预测基因组学基因芯片解决方案

Jong Bhak, PhD, CEO, Clinomics; Professor of Biomedical Engineering, Ulsan National Institute of Science and Technology; Genome Lab and Korean Genomics Center

Expanding genetic disease testing in Korea with customizable population genomics microarrays

Dushyant Singh Baghel, MD, CEO of Nucleome Informatics

Investigating inherited retinal disease in India using customized genotyping arrays

Tuan Cao, Co-founder and CEO Genetica

Decoding unique Asian lifestyle and disease variants through collaboration and custom genotyping arrays

Richard Pither, PhD, CEO of Cytox

Transforming Alzheimer’s disease characterization through genetic risk scoring

Alexandre Pereira, MD, PhD, São Paulo University Heart Institute; Leader of Human Genetics, Laboratory of Genetics and Molecular Cardiology; Head of Genetics Outpatient Clinic

Mining the multiethnic Brazilian population for genetic risk factors in cardiovascular disease and Sars-CoV-2 exposure

Vision of Polygenic Risk Scores in Health Care

Professor Peter Donnelly talks about the vision of polygenic risk scores in health care. Learn how polygenic risk scores enable early identification of individuals at higher lifetime risk of disease, to target screening or interventions. See Sir Professor Peter Donnelly's full presentation video on a vision for polygenic risk scores in health care

The FinnGen Research Project: Combining Genomics and Health Record Data to Understand Disease Mechanisms

Hear Dr. Palotie speak about the research goal to improve our understanding of disease mechanisms, specifically in chronic diseases that affect a large part of the population, because that’s the clue toward new therapies; we need to understand more about the disease. And how we do that is we use special populations like the Finnish population, which has a special population history, providing certain benefits. 

Bringing predictive genomics into a nationwide model: A spotlight on the Taiwan Precision Medicine Initiative

Dr. Kwok has been at the forefront of large-scale genomic studies. One of his most well-known undertakings was a collaboration between Kaiser Permanente and UCSF where scientists genotyped more than 100,000 Kaiser Permanente members. Today he is focused on two far-reaching goals. First, how to make precision medicine more precise by increasing the diversity of genomic databases. Second, how to sensibly incorporate genetic information into regular clinical practice. 

Integrating preemptive pharmacogenomics into health care.

Learn what Dr. Philip Empey, the Associate Director for Pharmacogenomics of the Pitt/UPMC Institute of Precision Medicine and Director of the University of Pittsburgh/Thermo Fisher Scientific Pharmacogenomics Center of Excellence has to say regarding the challenges to incorporate pharmacogenomics into routine clinical decision making.

Genotyping Techniques Used by Researchers

Importance of imputation accuracy in the selection of human genotyping array

Microarrays: an essential tool for predictive genomics

Current state of pharmacogenomics and its future

Pharmacogenomics in precision medicine: pathways to ease adoption

Navigate the technology landscape in predictive genomics

Qatar Genome Program: Building the next generation of infrastructures to test the value of predictive genomics

The future of predictive genomics in Israel

Predictive genomics webinar series: Global experts discuss genomics innovations that are changing future of healthcare

Preemptive pharmacogenomic insights to improve drug treatment for mental health disorders

Smarter is better than larger: How imputation-aware whole-genome genotyping bridges the gap between sequencing and targeted panels

The A to Z of microarrays - evolution of a revolutionary solution

Microarrays: An important tool for predictive genomics

Navigating the technology landscape for population-scale predictive genomics and exploring strategies for disease risk and drug response research

Preemptive Pharmacogenomics-investigating the relationship between genotype and drug response.

Decoding large national genetic study design

 Flyer: Comprehensive solutions for your pharmacogenomics research

Brochure: Insights in disease risk and drug response - Axiom genotyping arrays for human studies

Brochure: Axiom PangenomiX and Axiom PangenomiX Plus arrays

Flyer: GeneTitan MC Fast Scan  Instrument

Predictive Genomics Powering the future of population and personalized health

Axiom Propel workflow: Elevate your genotyping to a grand scale

The Axiom Genotyping Solution

GeneTitan MC Fast Scan Instrument

Selection guide: Axiom Genotyping Solution for Human Genetics

Total solution: Your partner from sample to insights

Predictive Genomics and Microarray Tutorial Video

Learn about Predictive Genomics. The tutorial explain what Predictive Genomics, Population Genomics,  Pharmacogenomics and how Microarrays are used in these application areas.

Thermo Fisher Scientific Microarray Technology

The vision of Pharmacogenomics

The estimated annual cost of drug-related morbidity and mortality resulting from non-optimized medication therapy was $528.4 billion in the United States alone in 2016, equivalent to 16 percent of the country’s total health care expenditures. Pharmacogenomics, the understanding of how genes impact an individual’s response to medications, promises to change that. Significant progress has been made in using genomics to determine the safest, most effective course of treatments for individuals and, as these programs scale and go mainstream, we have reached a tipping point where they are starting to deliver on their promise of improving the health of communities and significantly lowering healthcare costs. 

Predictive Genomics and Microarray Tutorial Video

Learn about Predictive Genomics. The tutorial explain what Predictive Genomics, Population Genomics,  Pharmacogenomics and how Microarrays are used in these application areas.

Customer & Expert Testimonial Videos

What Should Be Reported to Participants in a Genomics Screening Program?

Several different types of information could be reported to participants in genomics-based screening programs. Rare inherited diseases might affect the participant themselves (autosomal dominant) or might not affect the participant but could affect their offspring (autosomal recessive). The risk for common complex diseases, such as diabetes or heart disease, may be assessed by polygenic risk scores that combine the effects of multiple low-impact variants. Pharmacogenetics captures variation in the way humans process drugs. Traits and ancestry do not have direct medical implications. Each of these categories has pros and cons when considering their inclusion in a genomics-based screening program. Genomics-based screening is not currently recommended for routine clinical use, but results may be returned to participants as part of an IRB-approved research study.

How Health Systems and National Initiatives Benefit from Genotype-Phenotype Research Databases

Building a monetizable data asset is the most common rationale for investing in a large genotype-phenotype database, but there are several other compelling reasons to move forward, including better risk segmentation and targeting interventions, participant engagement and activation, participant recruitment/retention, “marketing sizzle,” the perception of innovation, and the recruitment/retention of high-quality physician-researchers.

Investing in a large genotype-phenotype research database creates a monetizable data asset, particularly for pharmaceutical companies. The basic hypothesis is that genetics can help drug-makers identify and accelerate the development of relevant molecules that reach the right disease targets, while avoiding investments in programs based on less well-validated targets.

The Impact of Genetic Diversity on the Future of Health and Medicine

Personalizing health by tailoring treatments and predicting disease risk is predicated on understanding individual variation related to disease, behavioral and environmental factors. Global initiatives have taken aim at collecting comprehensive genetic, biologic and clinical data. Unfortunately, the majority of these initiatives primarily include people of European descent, creating inequities in non-European populations. If health systems, governments and academic research institutes want to better serve their communities, citizens and research efforts, population-based biobanks need to be representative of people with different genetic backgrounds, including marginalized and hard-to-reach groups. Failure to do this will lead to further inequities in health care.

The selection of publications and posters below focuses on large-scale predictive genomic studies citing the use of the Axiom whole-genome microarray platform.