Innovation Forum 2022

BCG Digital Ventures, part of the BCG X tech-build and design business unit, helps the world’s most influential organizations drive the next wave of innovation. As the industry’s leading business builder, we partner closely with 400+ clients to invent, launch, and scale innovative businesses. Today, we have launched nearly 200 businesses with an unmatched success rate industrywide.

The future of pharma lies in its ability to leverage data and make data-informed decisions. Collecting high-quality data without impacting scientists’ productivity is the first challenge. To tackle this challenge, LabTwin – the world’s first voice-powered digital lab assistant designed for scientists – enables hands-free data capture and exchange with informatics systems at the point of experimentation. This revolutionizes how scientists interact with their digital lab ecosystem and allows real-time data collection and immediate access to information from the bench while performing experiments.

Guests: Kathrin Heinzmann (Scientist at Cancer Research, UK), Phil Daschner (NIH), Alexandra Boitor (EACR)

Modarator: Carola Schade

BCG Digital Ventures, part of the BCG X tech-build and design business unit, helps the world’s most influential organizations drive the next wave of innovation. As the industry’s leading business builder, we partner closely with 400+ clients to invent, launch, and scale innovative businesses. Today, we have launched nearly 200 businesses with an unmatched success rate industrywide.

The future of pharma lies in its ability to leverage data and make data-informed decisions. Collecting high-quality data without impacting scientists’ productivity is the first challenge. To tackle this challenge, LabTwin – the world’s first voice-powered digital lab assistant designed for scientists – enables hands-free data capture and exchange with informatics systems at the point of experimentation. This revolutionizes how scientists interact with their digital lab ecosystem and allows real-time data collection and immediate access to information from the bench while performing experiments.

Guests: Kathrin Heinzmann (Scientist at Cancer Research, UK), Phil Daschner (NIH), Alexandra Boitor (EACR)

Modarator: Carola Schade

Measurable residual disease (MRD) is the most important post-treatment predictor of outcome in patients with adult myeloid leukemia (AML). While flow cytometry-based methods for MRD detection are well-established clinically, molecular methods of MRD detection are still in research development. The use of digital PCR for highly sensitive monitoring of AML-associated mutations in patients on a variety of treatment plans will be discussed, as well as its predictive value for relapse. Bone marrow and cell-free DNA-based MRD will be explored. We will also  demonstrate the value of multiplexing assays for simultaneous detection of multiple mutations in limiting patient samples.

Allograft cells undergoing apoptosis or necrosis release cell-free DNA that is genetically different from cfDNA released from recipient cells. We developed digital PCR-based assays to discriminate donor and recipient cfDNA for absolute quantification without sequencing, and to evaluate analytical performance.

45 CNV assays were developed with median zero copy allelic frequency 0.52 (IQR 0.43–0.59), one copy allelic frequency 0.41 (0.36–0.43), and two copy allelic frequency 0.08 (0.05–0.13). The assays performed linearly across the range <6–1280 copies/mL. LOB was 0 copies/mL, LOD was 6 copies/mL, and LOQ was 8 copies/mL.

This panel permits quantification of donor and recipient targets in cfDNA post-transplant. The CNV allelic frequencies maximise informativity and permit quantification against a negative background, unlike SNP-based approaches. In contrast to sequencing, dPCR permits rapid, direct quantification of the absolute concentration (copies/mL) of donor-derived cfDNA and total cell-free DNA, from which the relative measure of donor fraction (%) can be calculated.

Unique amino acid sequences at the junctions of fusion proteins translated from chimeric RNAs form neoantigenic peptide regions that can be developed to expand the potential repertoire of targets for therapeutic vaccines. We present a framework to identify immunogenic neoantigen candidates from fusion transcripts that can serve as targets for developing vaccines for the treatment and prevention of cancer. Our platform is based on two pipelines. The first rescues discordant paired-end reads discarded from high-throughput sequencing to build a database of chimeric RNAs from cancer samples. Major Open Reading Frames (ORFs) predicted from the RNA fusions from the database are processed through MHC binding predictor (MHCnuggets), a high-throughput MHC Class I and II neoantigen binding prediction program developed by Karchin et al. 2020. The second pipeline utilizes both well-characterized and rare MHC alleles to generate immunogenic neopeptides rank-ordered based on binding affinity measurements from in vitro experiments (half-maximal affinity or IC50). We present 20 novel fusions from 75 breast tumors, each from 3 subtypes TNBC, HER2+, and HR+. We also present a 3833 bp chimeric RNA resulting from readthrough transcription of a pseudogene into a gene located immediately 3’ followed by transplicing between exons 12 and 2. A total of 15 different 8-mer neoantigen peptides discovered from the fusion were predicted to bind to 35 unique MHC class I alleles with a binding affinity of IC50<500nM. All 15 peptides were assessed through an in vitro Enzyme-Linked Immunospot (ELISpot) assay and tested for CD8+ T cell response. The peptides determined to have the highest immunogenicity through the ELISpot Assay can serve as targets for developing tumor vaccines for breast cancer.

While circulating cell-free DNA (ccfDNA), and to some extent circulating tumor cells (CTCs) from blood are routinely used as analytes in liquid biopsy cancer research applications, circulating cell-free RNA (ccfRNA) has recently also gained relevance for biomarker studies. The combination of insights from different analytes promises increased understanding of molecular processes in tumor biology. However, there are still challenges to overcome in the preanalytical workflow, such as defining suitable blood collection tubes for optimal assay sensitivity. In this session, we show the multianalyte use of the PAXgene Blood ccfDNA Tube (RUO) for plasma extraction as part of a liquid biopsy workflow. Learning objectives: the need for blood stabilization for ccfDNA analysis and impact on assay sensitivity and multianalyte applications for liquid biopsy research.

Prostate cancer (PCa) is a major cause of disease and mortality among men worldwide. In 2020, approximately 1.4 million men were diagnosed with PCa, and approximately 375,000 men died of PCa. We urgently need biomarkers for diagnosis, prognosis, therapy prediction, or therapy monitoring. Liquid biopsies, including cell-free DNA (cfDNA) and circulating tumor cells (CTCs), are valuable for studying such biomarkers and are minimally invasive. We investigated plasma cfDNA from 34 progressive PCa patients for sequence variants. We found that analysis of cfDNA and CTCs can provide complementary information that may in future support treatment decisions and choice of therapy options for advanced PCa patients. We also investigated protein expression of AR and AR-V7 in PCa patients. Immunohistochemical staining of specimens from 410 patients showed that AR-V7 protein in granular cytoplasmic structures is an independent prognostic factor for relapse-free survival.

Next-generation sequencing (NGS) tests encompassing multi-gene panels, whole-exome (WES), and whole-genome sequencing (WGS) are becoming an integral part of clinical diagnostics for hereditary cancers. However, analyzing and interpreting these panels can be incredibly time-consuming and complex.

Join Dr. Ana Krivokuca as she presents a use-case of how the Institute for Oncology and Radiology Serbia (IORS), a National Cancer Research Center, uses QCI Interpret, a clinical decision support software, in their NGS testing pipeline to annotate, assess, and interpret the clinical significance of germline variants in hereditary cancers.

Attendees will:

• Explore the challenges of variant classification, including the limitations of manual curation, handling of VUS, and incorporating guideline recommendations.
• Learn how the IORS uses QCI Interpret to evaluate genomic profiles of hereditary cancers and identify variants with clinical utility.
• Receive a demonstration of how QCI Interpret filters and prioritizes variants, transparently computes ACMG/AMP classifications, and auto-generates clinical reports with the latest evidence.

Prostate cancer (PCa) is a major cause of disease and mortality among men worldwide. In 2020, approximately 1.4 million men were diagnosed with PCa, and approximately 375,000 men died of PCa. We urgently need biomarkers for diagnosis, prognosis, therapy prediction, or therapy monitoring. Liquid biopsies, including cell-free DNA (cfDNA) and circulating tumor cells (CTCs), are valuable for studying such biomarkers and are minimally invasive. We investigated plasma cfDNA from 34 progressive PCa patients for sequence variants. We found that analysis of cfDNA and CTCs can provide complementary information that may in future support treatment decisions and choice of therapy options for advanced PCa patients. We also investigated protein expression of AR and AR-V7 in PCa patients. Immunohistochemical staining of specimens from 410 patients showed that AR-V7 protein in granular cytoplasmic structures is an independent prognostic factor for relapse-free survival.

Unique amino acid sequences at the junctions of fusion proteins translated from chimeric RNAs form neoantigenic peptide regions that can be developed to expand the potential repertoire of targets for therapeutic vaccines. We present a framework to identify immunogenic neoantigen candidates from fusion transcripts that can serve as targets for developing vaccines for the treatment and prevention of cancer. Our platform is based on two pipelines. The first rescues discordant paired-end reads discarded from high-throughput sequencing to build a database of chimeric RNAs from cancer samples. Major Open Reading Frames (ORFs) predicted from the RNA fusions from the database are processed through MHC binding predictor (MHCnuggets), a high-throughput MHC Class I and II neoantigen binding prediction program developed by Karchin et al. 2020. The second pipeline utilizes both well-characterized and rare MHC alleles to generate immunogenic neopeptides rank-ordered based on binding affinity measurements from in vitro experiments (half-maximal affinity or IC50). We present 20 novel fusions from 75 breast tumors, each from 3 subtypes TNBC, HER2+, and HR+. We also present a 3833 bp chimeric RNA resulting from readthrough transcription of a pseudogene into a gene located immediately 3’ followed by transplicing between exons 12 and 2. A total of 15 different 8-mer neoantigen peptides discovered from the fusion were predicted to bind to 35 unique MHC class I alleles with a binding affinity of IC50<500nM. All 15 peptides were assessed through an in vitro Enzyme-Linked Immunospot (ELISpot) assay and tested for CD8+ T cell response. The peptides determined to have the highest immunogenicity through the ELISpot Assay can serve as targets for developing tumor vaccines for breast cancer.

Next-generation sequencing (NGS) tests encompassing multi-gene panels, whole-exome (WES), and whole-genome sequencing (WGS) are becoming an integral part of clinical diagnostics for hereditary cancers. However, analyzing and interpreting these panels can be incredibly time-consuming and complex.

Join Dr. Ana Krivokuca as she presents a use-case of how the Institute for Oncology and Radiology Serbia (IORS), a National Cancer Research Center, uses QCI Interpret, a clinical decision support software, in their NGS testing pipeline to annotate, assess, and interpret the clinical significance of germline variants in hereditary cancers.

Attendees will:

• Explore the challenges of variant classification, including the limitations of manual curation, handling of VUS, and incorporating guideline recommendations.
• Learn how the IORS uses QCI Interpret to evaluate genomic profiles of hereditary cancers and identify variants with clinical utility.
• Receive a demonstration of how QCI Interpret filters and prioritizes variants, transparently computes ACMG/AMP classifications, and auto-generates clinical reports with the latest evidence.

While circulating cell-free DNA (ccfDNA), and to some extent circulating tumor cells (CTCs) from blood are routinely used as analytes in liquid biopsy cancer research applications, circulating cell-free RNA (ccfRNA) has recently also gained relevance for biomarker studies. The combination of insights from different analytes promises increased understanding of molecular processes in tumor biology. However, there are still challenges to overcome in the preanalytical workflow, such as defining suitable blood collection tubes for optimal assay sensitivity. In this session, we show the multianalyte use of the PAXgene Blood ccfDNA Tube (RUO) for plasma extraction as part of a liquid biopsy workflow. Learning objectives: the need for blood stabilization for ccfDNA analysis and impact on assay sensitivity and multianalyte applications for liquid biopsy research.

Measurable residual disease (MRD) is the most important post-treatment predictor of outcome in patients with adult myeloid leukemia (AML). While flow cytometry-based methods for MRD detection are well-established clinically, molecular methods of MRD detection are still in research development. The use of digital PCR for highly sensitive monitoring of AML-associated mutations in patients on a variety of treatment plans will be discussed, as well as its predictive value for relapse. Bone marrow and cell-free DNA-based MRD will be explored. We will also  demonstrate the value of multiplexing assays for simultaneous detection of multiple mutations in limiting patient samples.

Allograft cells undergoing apoptosis or necrosis release cell-free DNA that is genetically different from cfDNA released from recipient cells. We developed digital PCR-based assays to discriminate donor and recipient cfDNA for absolute quantification without sequencing, and to evaluate analytical performance.

45 CNV assays were developed with median zero copy allelic frequency 0.52 (IQR 0.43–0.59), one copy allelic frequency 0.41 (0.36–0.43), and two copy allelic frequency 0.08 (0.05–0.13). The assays performed linearly across the range <6–1280 copies/mL. LOB was 0 copies/mL, LOD was 6 copies/mL, and LOQ was 8 copies/mL.

This panel permits quantification of donor and recipient targets in cfDNA post-transplant. The CNV allelic frequencies maximise informativity and permit quantification against a negative background, unlike SNP-based approaches. In contrast to sequencing, dPCR permits rapid, direct quantification of the absolute concentration (copies/mL) of donor-derived cfDNA and total cell-free DNA, from which the relative measure of donor fraction (%) can be calculated.

Digital PCR (dPCR) has become a more established technology over the last decade, with several instrument formats available. Yet, given the mature status of real-time PCR and the broad opportunities offered by the latest sequencing technologies, it is often unclear what dPCR can contribute. This presentation will explore how dPCR has changed over the last decade, outline the advantages and look at how it can contribute to advancing molecular analysis. It will also discuss the new digital MIQE guidelines and how they can help maximize the impact of research using dPCR.

The major obstacle to reaching a cure for HIV is establishing a persistent latent reservoir that is unaffected by current HIV treatment regimens and causes viral rebound upon therapy cessation. Over the past years, digital PCR (dPCR) methods gained rapid interest in accurately measuring and monitoring the (intact) HIV reservoir size, especially in the context of clinical trials, which aim to determine reservoir dynamics or changes upon curative treatment challenges.

Here, Dr. Trypsteen will present the combination of up to five HIV assays into a single “rainbow” dPCR reaction and evaluate its benefits and technical performance on cell line and patient-derived samples. These assays can increase the information retrieved from a single dPCR readout over the current existing assays, reducing cost and time and improving the estimation of the intact latent HIV reservoir, which is the origin and cause of viral rebound.

In 2009, a group of qPCR experts published the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines for reproducible experiments. Those guidelines shaped present-day qPCR, which is considered a gold standard technique in molecular biology. Fast forward to 2013, dPCR also took advantage of the publication of the Minimum Information for Publication of Quantitative Digital PCR Experiments (dMIQE) guidelines to ensure global standardization. A new version of the dMIQE guidelines was published in 2020, considering the increasing number of applications and the introduction of new platforms.

In this session, we will address practical considerations for: 

• Template treatment
• Assay design
• Thermal cycling protocols
• Assay validation

Digital PCR (dPCR) has become a more established technology over the last decade, with several instrument formats available. Yet, given the mature status of real-time PCR and the broad opportunities offered by the latest sequencing technologies, it is often unclear what dPCR can contribute. This presentation will explore how dPCR has changed over the last decade, outline the advantages and look at how it can contribute to advancing molecular analysis. It will also discuss the new digital MIQE guidelines and how they can help maximize the impact of research using dPCR.

The major obstacle to reaching a cure for HIV is establishing a persistent latent reservoir that is unaffected by current HIV treatment regimens and causes viral rebound upon therapy cessation. Over the past years, digital PCR (dPCR) methods gained rapid interest in accurately measuring and monitoring the (intact) HIV reservoir size, especially in the context of clinical trials, which aim to determine reservoir dynamics or changes upon curative treatment challenges.

Here, Dr. Trypsteen will present the combination of up to five HIV assays into a single “rainbow” dPCR reaction and evaluate its benefits and technical performance on cell line and patient-derived samples. These assays can increase the information retrieved from a single dPCR readout over the current existing assays, reducing cost and time and improving the estimation of the intact latent HIV reservoir, which is the origin and cause of viral rebound.

In 2009, a group of qPCR experts published the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines for reproducible experiments. Those guidelines shaped present-day qPCR, which is considered a gold standard technique in molecular biology. Fast forward to 2013, dPCR also took advantage of the publication of the Minimum Information for Publication of Quantitative Digital PCR Experiments (dMIQE) guidelines to ensure global standardization. A new version of the dMIQE guidelines was published in 2020, considering the increasing number of applications and the introduction of new platforms.

In this session, we will address practical considerations for: 

• Template treatment
• Assay design
• Thermal cycling protocols
• Assay validation

Antibiotic resistance is one of the most urgent threats to global health. The effects of antibiotic resistance are already in catastrophic proportions, with over 1.2 million people dying of resistant infections in 2019. Antibiotic use increases in resistant bacteria, while antibiotic resistant genes (ARGs) can also spread among bacteria. This is why resistance hotspots develop where antibiotic use is high and bacteria, especially pathogens, can silently share ARGs in the environment. Monitoring ARGs is a prerequisite in identifying and characterizing sources of resistance and developing effective strategies to mitigate their development and spread. The biotechnology company Resistomap Oy aims to help researchers monitor ARGs and genes associated with pathogens from environmental samples such as wastewater, soils, manure and stool samples. Resistomap's mission is to mitigate the spread of antibiotic resistance by providing robust tools for monitoring.

Uncovering the depths of soil microbial communities is the new frontier for regenerative agriculture. It’s no longer enough to know which microbes are present, but we need to know what these microorganisms mean – and to go further – how to use this information to boost productivity and defend the crop in a sustainable way. The microbiome is the key tool for understanding and using nature for the longevity of land use. In this presentation, we’ll talk about the numerous applications and interpretations of our research results.

The origin of eukaryotes approximately two billion years ago was one of the most impactful evolutionary processes in the history of life on Earth. This event likely took place through the symbiosis of an archaeal host cell and an intracellular bacterium, which eventually became the mitochondrion. Since the discovery of the archaea domain, sequencing-based techniques have not only broadened our knowledge of the diversity of archaea but also highlighted their importance for evolution. The closest prokaryotic relatives of modern eukaryotes are the recently discovered group of Asgard archaea. While genome-based information shows their eukaryote-specific features, detailed information on the physiology of Asgard archaea is still missing. Using samples from around the world, we are trying to enrich and isolate those archaea. By combining classical approaches with high-throughput cultivation methods and modern ‘omics techniques, we aim to explore, expand and reshape the tree of life.

Fermentation is the world’s oldest science. Bacteria and yeast have incredibly diverse functions to convert base ingredients into unique fermented foods that are a staple of diets in many cultures. While we may be familiar with many of the prominent players in sourdough, yogurt or miso, there are thousands of unique ferments that are yet to be studied. Each of these is home to microbes that assemble, exist and transform food in unique ways. Throughout this project, 360 unique fermented food samples from six countries were collected and sequenced.

To promote the health of preterm babies, a better understanding of the interplay between gut microbes, host and diet is needed. For example, specific oligosaccharides from the mother’s milk can module the gut microbiome and significantly reduce the risk of necrotizing enterocolitis and late-onset sepsis in the infant. Based on the multi-omicanalysis of clinical samples, together with microbiome and metabolomic profiling and basic microbiology, we linked diet-microbe-host interactions to a range of health and disease outcomes. We also use a human intestinal organoid model system to advance our gut microbiome work. This session, will cover how the microbiome develops in infants and discuss the potential to develop novel disease biomarkers and targeted therapeutic interventions while focusing on promoting the health of preterm infants.

During sexual contact, material from the genital microbiome could be transferred between both partners. This hypothesis could serve as an alternative test when collecting forensic evidence in sexual assault cases. Our project investigates the genital microbiome by deep metagenomic sequencing followed by developing a real-time PCR assay for specific genital microbial taxa with the potential to be signature organisms for the female and male genital microbiomes. Pre- and post-coital genital samples from 19 female and male volunteers were collected, extracted, quantified and amplified using the qPCR-based methodology. Four Lactobacilli species were investigated and tested for vaginal specificity that have been proposed to make up the bulk of a healthy vaginal microbiome, whereas Gardnerella vaginalis is solely present in females with bacterial vaginosis. Results show that during sexual contact, bacteria are transferred that can be used in forensic science to objectively prove if sexual contact occurred.

The human gut microbiota affects human metabolism, while at the same time, our nutrient intake affects the microbes in the human gut. To study how food and pharmaceutical compounds impact the human gut microbiota, sophisticated, dynamic and computer-controlled in vitro models of the gastrointestinal tract have been developed. The colon model mimics the physiological parameters in the large intestine and uses a standardized microbiota to investigate the microbial composition and activity in a mechanistic manner. For this, we isolate the genomic DNA from fresh and frozen fecal samples, soil, fruits and vegetables since they contain microbes that can potentially colonize our gut. Our work focuses on the modulation of a healthy microbiota with the aim of providing dietary advice to customers on how to improve their health.

Antibiotic resistance is one of the most urgent threats to global health. The effects of antibiotic resistance are already in catastrophic proportions, with over 1.2 million people dying of resistant infections in 2019. Antibiotic use increases in resistant bacteria, while antibiotic resistant genes (ARGs) can also spread among bacteria. This is why resistance hotspots develop where antibiotic use is high and bacteria, especially pathogens, can silently share ARGs in the environment. Monitoring ARGs is a prerequisite in identifying and characterizing sources of resistance and developing effective strategies to mitigate their development and spread. The biotechnology company Resistomap Oy aims to help researchers monitor ARGs and genes associated with pathogens from environmental samples such as wastewater, soils, manure and stool samples. Resistomap's mission is to mitigate the spread of antibiotic resistance by providing robust tools for monitoring.

Uncovering the depths of soil microbial communities is the new frontier for regenerative agriculture. It’s no longer enough to know which microbes are present, but we need to know what these microorganisms mean – and to go further – how to use this information to boost productivity and defend the crop in a sustainable way. The microbiome is the key tool for understanding and using nature for the longevity of land use. In this presentation, we’ll talk about the numerous applications and interpretations of our research results.

The origin of eukaryotes approximately two billion years ago was one of the most impactful evolutionary processes in the history of life on Earth. This event likely took place through the symbiosis of an archaeal host cell and an intracellular bacterium, which eventually became the mitochondrion. Since the discovery of the archaea domain, sequencing-based techniques have not only broadened our knowledge of the diversity of archaea but also highlighted their importance for evolution. The closest prokaryotic relatives of modern eukaryotes are the recently discovered group of Asgard archaea. While genome-based information shows their eukaryote-specific features, detailed information on the physiology of Asgard archaea is still missing. Using samples from around the world, we are trying to enrich and isolate those archaea. By combining classical approaches with high-throughput cultivation methods and modern ‘omics techniques, we aim to explore, expand and reshape the tree of life.

Fermentation is the world’s oldest science. Bacteria and yeast have incredibly diverse functions to convert base ingredients into unique fermented foods that are a staple of diets in many cultures. While we may be familiar with many of the prominent players in sourdough, yogurt or miso, there are thousands of unique ferments that are yet to be studied. Each of these is home to microbes that assemble, exist and transform food in unique ways. Throughout this project, 360 unique fermented food samples from six countries were collected and sequenced.

The human gut microbiota affects human metabolism, while at the same time, our nutrient intake affects the microbes in the human gut. To study how food and pharmaceutical compounds impact the human gut microbiota, sophisticated, dynamic and computer-controlled in vitro models of the gastrointestinal tract have been developed. The colon model mimics the physiological parameters in the large intestine and uses a standardized microbiota to investigate the microbial composition and activity in a mechanistic manner. For this, we isolate the genomic DNA from fresh and frozen fecal samples, soil, fruits and vegetables since they contain microbes that can potentially colonize our gut. Our work focuses on the modulation of a healthy microbiota with the aim of providing dietary advice to customers on how to improve their health.

To promote the health of preterm babies, a better understanding of the interplay between gut microbes, host and diet is needed. For example, specific oligosaccharides from the mother’s milk can module the gut microbiome and significantly reduce the risk of necrotizing enterocolitis and late-onset sepsis in the infant. Based on the multi-omicanalysis of clinical samples, together with microbiome and metabolomic profiling and basic microbiology, we linked diet-microbe-host interactions to a range of health and disease outcomes. We also use a human intestinal organoid model system to advance our gut microbiome work. This session, will cover how the microbiome develops in infants and discuss the potential to develop novel disease biomarkers and targeted therapeutic interventions while focusing on promoting the health of preterm infants.

Viral vectors used for gene and cell therapies have the potential to deliver life-saving treatments for millions of people. However, to realize this potential, vector manufacturing must reach scales far beyond what is possible today. This creates an urgent need for new manufacturing processes and emphasizes the importance of the analytical assays used to characterize the behavior of vectors in the manufacturing process and ultimately in vivo.

Join our panel of experts as they discuss:

• How challenging is it to plan and build the future of viral vector manufacturing today?
• What strategies willsolve the analytical bottleneck to meet future demand?
• What are the tools driving iterative process refinements?
• How different is the analytical toolkit for characterizing in vivo behavior of vectors?
• How did QIAcuity impact planning/thinking? What doors opened by adopting a higher throughput digital PCR system, and what’s next?

We cover the full spectrum from discovery to clinical assay development, significantly accelerating your projects. With our expertise at your fingertips, you can access a wide breadth of technologies, chemistries and workflows globally recognized for quality. Optimal experimental design is ensured during pre-consultation by our expert scientific services team, backed by our track record of product and service development. To answer your biological question in the best possible way, our highly skilled design experts will tailor your qPCR, dPCR or next-generation sequencing assay to fit your specific needs. Furthermore, you will get the high-value insights you're looking for from the industry‘s most comprehensive and up-to-date knowledgebases.

We have been collaborating with pharmaceutical partners for more than 15 years to develop companion diagnostics (CDx). We got 10 PMA approvals granted by the FDA and registered and commercialized the CDx assays globally in all target markets of pharma. A broad technology portfolio including qPCR, digital PCR, and NGS is available to meet any CDx requirement, building on tissue and liquid biopsies with the highest sensitivities. Starting at translational medicine, a drug development program that requires a companion diagnostic can still be complex. We need to reduce this complexity to de-risk the clinical drug-diagnostic development program and facilitate immediate patient access to testing when new drugs and tests come to market.

Metastases are the primary cause of cancer death. Bone is a major site of metastasis in several cancers, with breast and prostate cancer being most affected. With no effective therapies available, bone metastases are currently incurable and a high unmet medical need. Only about 5% of cancer patients with bone metastases are alive 5 years after the diagnosis. OncoBone Therapeutics aims to develop novel therapies for bone metastasis utilizing a novel osteoimmuno-oncology (OIO) concept. OIO refers to interactions of cancer, bone and immune cells, three compartments important in regulating growth of bone metastases that should all be targeted when developing effective and safe therapies for bone metastases. In this presentation, we discuss the science behind our most advanced therapeutic asset and give insights to our future development goals.

Although decoding the human genome through the invention of DNA sequencing has ushered in a new era of biomedical sciences, this blueprint is not enough. We are defined by more than our genes: to understand the human body, we must understand the proteins that actually perform our day-to-day functions--and malfunctions. Glyphic Biotechnologies is decoding the human proteome through full coverage, de novo protein sequencing at single molecule resolutions, advancing beyond the decades old technologies based on mass spectrometry and ELISAs.This platform will enable the development of novel therapeutics and diagnostics and, ultimately, a deeper understanding of human biology.

In disease research, understanding the key genes involved and how they interact to drive disease occurrence or severity is extremely valuable. Discovering previously unknown gene-disease relationships helps us gain insights to develop new potential therapies. To this end, we applied machine learning (ML) to our QIAGEN Knowledge Graph (QKG) to predict novel gene-disease associations. A research team at MicroMatrices, who study familial paraganglioma, investigated potential new targets by identifying differentially expressed genes using laser dissection targeted transcriptomics analysis in tumor vs. normal tissue. They compared the changes found in their case study with predicted gene alterations made by our ML process and found potential new drug targets and candidate drugs. Their treatment hypotheses can be tested in a 3D model of paraganglioma using SpheroMatrices microtissue array (microTMA) technology.

If you'd like to explore a new way to identify potential new drug targets, you won't want to miss this unique opportunity to learn from industry experts about:

• How machine learning used known relationships in the QKG to infer hidden relationships between potential targets and diseases
• A library of 1500 disease networks available in QIAGEN Ingenuity Pathway Analysis (IPA)
• MicroMatrices' research into paraganglioma and evaluation of novel gene associations predicted by our disease network
• Opportunities to verify new drug targets for paraganglioma as well as potential targets in other diseases

The following topics will be covered in this webinar:

• An overview of the RNA-based Xerna TME^TM Panel and its key biological features.
• The development and validation of the Xerna TME^TM Panel.
• New data presented at ESMO 2022
• Clinical and research applications of the XernaTME^TM Panel to support multiple oncology therapeutics, particularly immune checkpoint inhibitors and anti-angiogenic agents, across a variety of tumor types.
• Future development of the XernaTME^TM Panel as an RUO and CDx assay platform.

Who should attend and benefits of attending:

• Researchers and clinical investigators interested in learning about this novel, RNA-based precision medicine platform are encouraged to attend.
• Participants will achieve a greater understanding of how the XERNA TME^TM Panel can be used to understand the dominant biology of the tumor microenvironment and align to particular therapeutic modalities.

High-quality biomedical relationships knowledge is the cornerstone of modern and innovative data- and analytics-driven drug discovery. Yet this knowledge is locked in thousands of publications and dozens of databases. This session will show you how to unlock this knowledge and use it to strengthen your efforts in data science-driven drug discovery.

In this session, you'll learn about:

• High-quality biomedical relationships knowledge – what it is and how to access it
• Knowledge graphs and knowledge graph analysis
• Artificial intelligence (AI)-driven target identification and drug repositioning using knowledge graphs and biomedical relationships
• Disease subtyping and biomarker identification based on functional features
• Target, disease and drug intelligence portals: Application development and data integration leveraging biomedical relationships

Don't miss this opportunity to discover how to give your drug discovery programs a data science-driven advantage by leveraging high-quality biomedical relationships knowledge.

Viral vectors used for gene and cell therapies have the potential to deliver life-saving treatments for millions of people. However, to realize this potential, vector manufacturing must reach scales far beyond what is possible today. This creates an urgent need for new manufacturing processes and emphasizes the importance of the analytical assays used to characterize the behavior of vectors in the manufacturing process and ultimately in vivo.

Join our panel of experts as they discuss:

• How challenging is it to plan and build the future of viral vector manufacturing today?
• What strategies willsolve the analytical bottleneck to meet future demand?
• What are the tools driving iterative process refinements?
• How different is the analytical toolkit for characterizing in vivo behavior of vectors?
• How did QIAcuity impact planning/thinking? What doors opened by adopting a higher throughput digital PCR system, and what’s next?

We cover the full spectrum from discovery to clinical assay development, significantly accelerating your projects. With our expertise at your fingertips, you can access a wide breadth of technologies, chemistries and workflows globally recognized for quality. Optimal experimental design is ensured during pre-consultation by our expert scientific services team, backed by our track record of product and service development. To answer your biological question in the best possible way, our highly skilled design experts will tailor your qPCR, dPCR or next-generation sequencing assay to fit your specific needs. Furthermore, you will get the high-value insights you're looking for from the industry‘s most comprehensive and up-to-date knowledgebases.

We have been collaborating with pharmaceutical partners for more than 15 years to develop companion diagnostics (CDx). We got 10 PMA approvals granted by the FDA and registered and commercialized the CDx assays globally in all target markets of pharma. A broad technology portfolio including qPCR, digital PCR, and NGS is available to meet any CDx requirement, building on tissue and liquid biopsies with the highest sensitivities. Starting at translational medicine, a drug development program that requires a companion diagnostic can still be complex. We need to reduce this complexity to de-risk the clinical drug-diagnostic development program and facilitate immediate patient access to testing when new drugs and tests come to market.

Metastases are the primary cause of cancer death. Bone is a major site of metastasis in several cancers, with breast and prostate cancer being most affected. With no effective therapies available, bone metastases are currently incurable and a high unmet medical need. Only about 5% of cancer patients with bone metastases are alive 5 years after the diagnosis. OncoBone Therapeutics aims to develop novel therapies for bone metastasis utilizing a novel osteoimmuno-oncology (OIO) concept. OIO refers to interactions of cancer, bone and immune cells, three compartments important in regulating growth of bone metastases that should all be targeted when developing effective and safe therapies for bone metastases. In this presentation, we discuss the science behind our most advanced therapeutic asset and give insights to our future development goals.

Although decoding the human genome through the invention of DNA sequencing has ushered in a new era of biomedical sciences, this blueprint is not enough. We are defined by more than our genes: to understand the human body, we must understand the proteins that actually perform our day-to-day functions--and malfunctions. Glyphic Biotechnologies is decoding the human proteome through full coverage, de novo protein sequencing at single molecule resolutions, advancing beyond the decades old technologies based on mass spectrometry and ELISAs. This platform will enable the development of novel therapeutics and diagnostics and, ultimately, a deeper understanding of human biology.

In disease research, understanding the key genes involved and how they interact to drive disease occurrence or severity is extremely valuable. Discovering previously unknown gene-disease relationships helps us gain insights to develop new potential therapies. To this end, we applied machine learning (ML) to our QIAGEN Knowledge Graph (QKG) to predict novel gene-disease associations. A research team at MicroMatrices, who study familial paraganglioma, investigated potential new targets by identifying differentially expressed genes using laser dissection targeted transcriptomics analysis in tumor vs. normal tissue. They compared the changes found in their case study with predicted gene alterations made by our ML process and found potential new drug targets and candidate drugs. Their treatment hypotheses can be tested in a 3D model of paraganglioma using SpheroMatrices microtissue array (microTMA) technology.

If you'd like to explore a new way to identify potential new drug targets, you won't want to miss this unique opportunity to learn from industry experts about:

• How machine learning used known relationships in the QKG to infer hidden relationships between potential targets and diseases
• A library of 1500 disease networks available in QIAGEN Ingenuity Pathway Analysis (IPA)
• MicroMatrices' research into paraganglioma and evaluation of novel gene associations predicted by our disease network
• Opportunities to verify new drug targets for paraganglioma as well as potential targets in other diseases

The following topics will be covered in this webinar:

• An overview of the RNA-based Xerna TME^TM Panel and its key biological features.
• The development and validation of the Xerna TME^TM Panel.
• New data presented at ESMO 2022
• Clinical and research applications of the XernaTME^TM Panel to support multiple oncology therapeutics, particularly immune checkpoint inhibitors and anti-angiogenic agents, across a variety of tumor types.
• Future development of the XernaTME^TM Panel as an RUO and CDx assay platform.

Who should attend and benefits of attending:

• Researchers and clinical investigators interested in learning about this novel, RNA-based precision medicine platform are encouraged to attend.
• Participants will achieve a greater understanding of how the XERNA TME^TM Panel can be used to understand the dominant biology of the tumor microenvironment and align to particular therapeutic modalities.

High-quality biomedical relationships knowledge is the cornerstone of modern and innovative data- and analytics-driven drug discovery. Yet this knowledge is locked in thousands of publications and dozens of databases. This session will show you how to unlock this knowledge and use it to strengthen your efforts in data science-driven drug discovery.

In this session, you'll learn about:

• High-quality biomedical relationships knowledge – what it is and how to access it
• Knowledge graphs and knowledge graph analysis
• Artificial intelligence (AI)-driven target identification and drug repositioning using knowledge graphs and biomedical relationships
• Disease subtyping and biomarker identification based on functional features
• Target, disease and drug intelligence portals: Application development and data integration leveraging biomedical relationships

Don't miss this opportunity to discover how to give your drug discovery programs a data science-driven advantage by leveraging high-quality biomedical relationships knowledge.

Since the emergence of the COVID-19 pandemic, there has been an unprecedented interest in identifying ways to monitor and measure SARS-CoV-2 transmission. Many groups have focused on developing wastewater-based surveillance methods. By targeting wastewater, large populations of individuals can be monitored at different levels of scale in a passive, non-invasive and affordable way. By gathering information about fecal shedding of the virus in all persons, including symptomatic and asymptomatic individuals, viral trends in wastewater can be compared to trend observed from sequenced clinical specimens. The combination of clinical and wastewater-based sequencing can reveal the virus's response to treatment, drugs and vaccines in large populations.

Wastewater epidemiology for SARS-CoV-2 has two aims: (1) to monitor the abundance of the virus in wastewater samples over time, and (2) to determine the relative amounts of mutations associated with variants of concern (VOC) that are of interest to healthcare professionals.

This session focuses on efforts to perform next-generation sequencing (NGS) of SARS-CoV-2 from wastewater using both targeted and whole genome amplification approaches. Dr. Smyth will discuss how she and her colleagues leveraged their prior experiences and knowledge to overcome challenges associated with varying viral concentrations and viral genome fragmentation (degradation) characteristic of wastewater samples so that NGS and analysis could be conducted successfully. In particular, the utility of a new solution, the QIAseq DIRECT SARS-CoV-2 Kit, will be evaluated, revealing how its ultrafast workflow and novel primer design for RNA-seq library preparation make it highly suited for the detection of emerging new SARS-CoV-2 variants. Finally, other bottlenecks and barriers to viral NGS-based wastewater analysis will be discussed in relation to potential future pandemics.

By examining the host response to SARS-CoV-2 infection, we gain valuable insights into viral pathogenesis and COVID-19 progression. MicroRNAs (miRNAs), a class of small (18-22nt), non-coding RNAs, often play central roles in the host-pathogen interface and have been recognized as promising biomarkers of infectious disease. In this study, we profiled the circulating miRNAs from 10 longitudinally sampled COVID-19 patients and their age and gender-matched controls. We found 55 differentially expressed miRNAs in early-stage disease, including miRNAs with known pro- and anti-inflammatory roles. Machine learning also identified a three-miRNA signature of COVID-19 that predicted infection with 99.9% accuracy. This signature faded away as the patients recovered. When this three-miRNA signature was applied to ferrets (a common model of respiratory infections, including COVID-19), the signature predicted SARS-CoV-2 infection with 99.8% accuracy and could distinguish between SARS-CoV-2, influenza (H1N1), and uninfected controls with >95% accuracy.

This study demonstrates that SARS-CoV-2 infection results in a significant host miRNA response that aligns with our current knowledge of COVID-19-induced inflammation. Using a multivariate machine learning approach, we developed a robust miRNA biomarker signature of COVID-19. This signature could complement existing diagnostic tests by providing a new approach to detecting cases that might otherwise be missed.

Wastewater samples are challenging substrates for nucleic acid extraction, and the choice of extraction method determines the success of the downstream analysis. Extraction methods must address high levels of inhibitory substances and achieve extraordinary sensitivity to ensure accurate detection of SARS-CoV-2. Even with ideal extraction, SARS-CoV-2 RNA from wastewater often remains highly fragmented and at a low copy number. However, with optimized next-generation sequencing (NGS) techniques, it is still possible to produce NGS-ready, high-quality SARS-CoV-2 libraries from wastewater samples. Join this session to discover how to optimize sample extraction and NGS workflows for SARS-CoV-2 wastewater analysis. We’ll provide valuable tips and solutions for accurately detecting emerging SARS-CoV-2 variants.

Pathogen detection and surveillance have become a high priority in both healthcare and environmental settings for the safety of patients and the general public. The COVID-19 pandemic highlighted the need for strategies to identify and differentiate pathogen variants of concern. Municipalities employ NGS-based wastewater analysis to identify not only SARS-CoV-2 variants but also other viral and bacterial species as early alert systems of community health. In clinical settings where co-infections of two or more pathogens can complicate patient outcomes, such as with SARS-CoV-2 and influenza, microbial surveillance of patient areas may help circumvent disease outbreaks. Thus, there is a widespread need for targeted and sensitive variant detection through whole-genome characterization of a wide variety of microbial pathogens.

This session will discuss new probe-based NGS enrichment solutions. We’ll introduce our QIAseq xHYB Viral and Bacterial Panels, which use hybrid capture technology to provide high-sensitivity targeted whole-genome enrichment for detecting and sequencing:

• Respiratory viruses
• Sexually transmitted pathogens
• Antimicrobial-resistant (AMR) genes from bacteria
• Microbial bioreactor contaminants

Details of the content of these new panels and their performance across several different applications and sample types will be presented in this session.

Since January 2019, COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a health problem of major concern worldwide. The comparatively milder levels of disease severity caused by Omicron, the latest COVID-19 variant, in relation to previous variants of concern, has led to a relaxation in preventive measures. Correspondingly, the global population is currently seeing a resurgence of the disease.

In this study, we aim to measure the viral load of patients positive for Omicron subvariants to understand any correlation that exists between viral load and disease progression for specific subvariants. Viral load will be measured using the novel QIAcuity dPCR System, and all samples will be sequenced to determine the lineage of the variant affecting every patient.

A better understanding of the correlation between subvariants, viral load and disease progression is necessary to provide patients with relevant recommendations for quarantine and to determine effective testing strategies. Only with continuous efforts to follow virus evolution can we gain an understanding of viral fitness, infectivity patterns and clinical outcomes.

The potential rise of multiple new variants leading to a severe epidemic rebound is still a concern for the future. As we understand virus evolution and disease progression better, superior testing strategies to detect and isolate cases can be designed to allow the elimination of hotspot formation and contribute to controlling the spread of the disease.

Since the emergence of the COVID-19 pandemic, there has been an unprecedented interest in identifying ways to monitor and measure SARS-CoV-2 transmission. Many groups have focused on developing wastewater-based surveillance methods. By targeting wastewater, large populations of individuals can be monitored at different levels of scale in a passive, non-invasive and affordable way. By gathering information about fecal shedding of the virus in all persons, including symptomatic and asymptomatic individuals, viral trends in wastewater can be compared to trend observed from sequenced clinical specimens. The combination of clinical and wastewater-based sequencing can reveal the virus's response to treatment, drugs and vaccines in large populations.

Wastewater epidemiology for SARS-CoV-2 has two aims: (1) to monitor the abundance of the virus in wastewater samples over time, and (2) to determine the relative amounts of mutations associated with variants of concern (VOC) that are of interest to healthcare professionals.

This session focuses on efforts to perform next-generation sequencing (NGS) of SARS-CoV-2 from wastewater using both targeted and whole genome amplification approaches. Dr. Smyth will discuss how she and her colleagues leveraged their prior experiences and knowledge to overcome challenges associated with varying viral concentrations and viral genome fragmentation (degradation) characteristic of wastewater samples so that NGS and analysis could be conducted successfully. In particular, the utility of a new solution, the QIAseq DIRECT SARS-CoV-2 Kit, will be evaluated, revealing how its ultrafast workflow and novel primer design for RNA-seq library preparation make it highly suited for the detection of emerging new SARS-CoV-2 variants. Finally, other bottlenecks and barriers to viral NGS-based wastewater analysis will be discussed in relation to potential future pandemics.

By examining the host response to SARS-CoV-2 infection, we gain valuable insights into viral pathogenesis and COVID-19 progression. MicroRNAs (miRNAs), a class of small (18-22nt), non-coding RNAs, often play central roles in the host-pathogen interface and have been recognized as promising biomarkers of infectious disease. In this study, we profiled the circulating miRNAs from 10 longitudinally sampled COVID-19 patients and their age and gender-matched controls. We found 55 differentially expressed miRNAs in early-stage disease, including miRNAs with known pro- and anti-inflammatory roles. Machine learning also identified a three-miRNA signature of COVID-19 that predicted infection with 99.9% accuracy. This signature faded away as the patients recovered. When this three-miRNA signature was applied to ferrets (a common model of respiratory infections, including COVID-19), the signature predicted SARS-CoV-2 infection with 99.8% accuracy and could distinguish between SARS-CoV-2, influenza (H1N1), and uninfected controls with >95% accuracy.

This study demonstrates that SARS-CoV-2 infection results in a significant host miRNA response that aligns with our current knowledge of COVID-19-induced inflammation. Using a multivariate machine learning approach, we developed a robust miRNA biomarker signature of COVID-19. This signature could complement existing diagnostic tests by providing a new approach to detecting cases that might otherwise be missed.

Wastewater samples are challenging substrates for nucleic acid extraction, and the choice of extraction method determines the success of the downstream analysis. Extraction methods must address high levels of inhibitory substances and achieve extraordinary sensitivity to ensure accurate detection of SARS-CoV-2. Even with ideal extraction, SARS-CoV-2 RNA from wastewater often remains highly fragmented and at a low copy number. However, with optimized next-generation sequencing (NGS) techniques, it is still possible to produce NGS-ready, high-quality SARS-CoV-2 libraries from wastewater samples. Join this session to discover how to optimize sample extraction and NGS workflows for SARS-CoV-2 wastewater analysis. We’ll provide valuable tips and solutions for accurately detecting emerging SARS-CoV-2 variants.

Pathogen detection and surveillance have become a high priority in both healthcare and environmental settings for the safety of patients and the general public. The COVID-19 pandemic highlighted the need for strategies to identify and differentiate pathogen variants of concern. Municipalities employ NGS-based wastewater analysis to identify not only SARS-CoV-2 variants but also other viral and bacterial species as early alert systems of community health. In clinical settings where co-infections of two or more pathogens can complicate patient outcomes, such as with SARS-CoV-2 and influenza, microbial surveillance of patient areas may help circumvent disease outbreaks. Thus, there is a widespread need for targeted and sensitive variant detection through whole-genome characterization of a wide variety of microbial pathogens.

This session will discuss new probe-based NGS enrichment solutions. We’ll introduce our QIAseq xHYB Viral and Bacterial Panels, which use hybrid capture technology to provide high-sensitivity targeted whole-genome enrichment for detecting and sequencing:

• Respiratory viruses
• Sexually transmitted pathogens
• Antimicrobial-resistant (AMR) genes from bacteria
• Microbial bioreactor contaminants

Details of the content of these new panels and their performance across several different applications and sample types will be presented in this session.

Since January 2019, COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a health problem of major concern worldwide. The comparatively milder levels of disease severity caused by Omicron, the latest COVID-19 variant, in relation to previous variants of concern, has led to a relaxation in preventive measures. Correspondingly, the global population is currently seeing a resurgence of the disease.

In this study, we aim to measure the viral load of patients positive for Omicron subvariants to understand any correlation that exists between viral load and disease progression for specific subvariants. Viral load will be measured using the novel QIAcuity dPCR System, and all samples will be sequenced to determine the lineage of the variant affecting every patient.

A better understanding of the correlation between subvariants, viral load and disease progression is necessary to provide patients with relevant recommendations for quarantine and to determine effective testing strategies. Only with continuous efforts to follow virus evolution can we gain an understanding of viral fitness, infectivity patterns and clinical outcomes.

The potential rise of multiple new variants leading to a severe epidemic rebound is still a concern for the future. As we understand virus evolution and disease progression better, superior testing strategies to detect and isolate cases can be designed to allow the elimination of hotspot formation and contribute to controlling the spread of the disease.

The Chagos Archipelago in the central Indian Ocean is one of the largest and most remote marine-protected areas in the world. It comprises 55 tiny scattered islands gently lapped by some of the cleanest seawater ever recorded. Its location midway between the East African coast and the Western Indo-Pacific serves as a stepping stone for marine biodiversity in the region, offering a refuge for globally-important species such as turtles, sharks, coconut crabs and seabirds. The 60,000 square kilometers of coral reefs here provide one of the best examples of a relatively pristine contemporary reef system when wilderness habitats such as these have become increasingly rare. Yet even here, the pernicious effects of unsustainable human activity and reliance on single-use plastics have begun to leave their indelible mark.

In this session, I will give an illuminating overview of my research as a QIAGEN NGS Profile Award winner to study the world's rarest coral, highlighting my ongoing efforts to understand the bewildering and spectacular array of nature that abounds in this iconic marine reserve.

In recent years, sustainability has become a hot topic and has found its way into politics and economics. Politicians are now striving to reach the UN Sustainable Development Goals (SDGs), and companies are required to deliver Corporate Sustainability Reports. While politicians and companies have more substantial incentives and better tools to become more sustainable, academic institutions are often lagging. There are several valid reasons for this, such as a high turnover in university labs and a lack of financial capacities, standardized protocols, and knowledge about lab sustainability.

This sesion will cover:

• How the 9Rs of sustainability can be implemented in any laboratory environment
• Important strategies and sources for sustainable development
• What the sustainability teams at QIAGEN and the University of Bergen have done in recent years

Using some of these strategies, labs can easily become more sustainable in terms of energy and plastic consumption. This is not only more friendly on the environment but also more friendly to your research grants by freeing up financial resources. I will show you that change is possible; it just requires a little hard work and heart work.

Sustainability is a topic of increasing focus, also in science, where research generates significant amounts of waste and consumes a lot of energy. Many of us are making changes in our personal lives to reduce our ecological footprint, and there is a growing movement to also do this in the lab.

To contribute to these efforts and move toward a more eco-friendly approach in science, we will introduce the QIAwave product line. While maintaining the same performance, these kits use more environmentally friendly packaging than our standard kits, including removal of paper instructions and single-use spin column packaging. Buffers are offered as concentrates, and collection tubes are replaced with waste tubes made from 100% post-consumer recycled plastic. This reduction in packaging is only a first step; further developments will focus on the additional reduction of plastic components.

In this session, we will also share some small routines in the lab that can already have a positive impact, as well as excellent initiatives that encourage collaboration and idea-sharing.

My Green Lab is a non-profit organization with a mission to build a global culture of sustainability in science. While science supports the development of world-changing and life-saving breakthroughs every day, it is an unfortunate reality that scientific research itself also has a significant environmental impact. Labs use up to 10 times more energy than a commercial office building, four times more water, and produce over 5.5 million metric tons of plastic waste a year, 2% of global production. Therefore, it is important to consider the carbon impact of research as well as single-use plastic, both of which have a significant effect on the health of our oceans. Small changes in behavior in the lab can add up. In this session, we'll offer tips and tricks that you can implement in your lab today to help you reduce your environmental impact and join a global movement that is transforming science through sustainability.

The Chagos Archipelago in the central Indian Ocean is one of the largest and most remote marine-protected areas in the world. It comprises 55 tiny scattered islands gently lapped by some of the cleanest seawater ever recorded. Its location midway between the East African coast and the Western Indo-Pacific serves as a stepping stone for marine biodiversity in the region, offering a refuge for globally-important species such as turtles, sharks, coconut crabs and seabirds. The 60,000 square kilometers of coral reefs here provide one of the best examples of a relatively pristine contemporary reef system when wilderness habitats such as these have become increasingly rare. Yet even here, the pernicious effects of unsustainable human activity and reliance on single-use plastics have begun to leave their indelible mark.

In this session, I will give an illuminating overview of my research as a QIAGEN NGS Profile Award winner to study the world's rarest coral, highlighting my ongoing efforts to understand the bewildering and spectacular array of nature that abounds in this iconic marine reserve.

In recent years, sustainability has become a hot topic and has found its way into politics and economics. Politicians are now striving to reach the UN Sustainable Development Goals (SDGs), and companies are required to deliver Corporate Sustainability Reports. While politicians and companies have more substantial incentives and better tools to become more sustainable, academic institutions are often lagging. There are several valid reasons for this, such as a high turnover in university labs and a lack of financial capacities, standardized protocols, and knowledge about lab sustainability.

This sesion will cover:

• How the 9Rs of sustainability can be implemented in any laboratory environment
• Important strategies and sources for sustainable development
• What the sustainability teams at QIAGEN and the University of Bergen have done in recent years

Using some of these strategies, labs can easily become more sustainable in terms of energy and plastic consumption. This is not only more friendly on the environment but also more friendly to your research grants by freeing up financial resources. I will show you that change is possible; it just requires a little hard work and heart work.

Sustainability is a topic of increasing focus, also in science, where research generates significant amounts of waste and consumes a lot of energy. Many of us are making changes in our personal lives to reduce our ecological footprint, and there is a growing movement to also do this in the lab.

To contribute to these efforts and move toward a more eco-friendly approach in science, we will introduce the QIAwave product line. While maintaining the same performance, these kits use more environmentally friendly packaging than our standard kits, including removal of paper instructions and single-use spin column packaging. Buffers are offered as concentrates, and collection tubes are replaced with waste tubes made from 100% post-consumer recycled plastic. This reduction in packaging is only a first step; further developments will focus on the additional reduction of plastic components.

In this session, we will also share some small routines in the lab that can already have a positive impact, as well as excellent initiatives that encourage collaboration and idea-sharing.

My Green Lab is a non-profit organization with a mission to build a global culture of sustainability in science. While science supports the development of world-changing and life-saving breakthroughs every day, it is an unfortunate reality that scientific research itself also has a significant environmental impact. Labs use up to 10 times more energy than a commercial office building, four times more water, and produce over 5.5 million metric tons of plastic waste a year, 2% of global production. Therefore, it is important to consider the carbon impact of research as well as single-use plastic, both of which have a significant effect on the health of our oceans. Small changes in behavior in the lab can add up. In this session, we'll offer tips and tricks that you can implement in your lab today to help you reduce your environmental impact and join a global movement that is transforming science through sustainability.

The success of any presentation is greatly dependent on the communication and delivery skills of the presenter, including their ability to comfortably and dynamically connect with the audience. These skills can be learned and practiced.

In this workshop, you will gain some insights, tools and skills that will help you engage your audience and deliver your message in a powerful way so that it is not only heard but understood and remembered. Whether you are a novice or more experienced, you will walk away with tips and tricks to improve your skill set.

The success of any presentation is greatly dependent on the communication and delivery skills of the presenter, including their ability to comfortably and dynamically connect with the audience. These skills can be learned and practiced.

In this workshop, you will gain some insights, tools and skills that will help you engage your audience and deliver your message in a powerful way so that it is not only heard but understood and remembered. Whether you are a novice or more experienced, you will walk away with tips and tricks to improve your skill set.