Implementation of Genetic Analysis in Comprehensive Biobank - - PowerPoint PPT Presentation
Implementation of Genetic Analysis in Comprehensive Biobank Workflows for Basic Science, Clinical Research and Precision Medicine Applications Dr. Andrew Brooks COO, RUCDR Infinite Biologics Rutgers University www.brookslifesciences.com 1
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COO, RUCDR Infinite Biologics Rutgers University
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We now use biological samples to accomplish important activities to create better therapies:
The future of biosample collection and analysis promises a change in how we think about healthcare:
genetics and environment
early as 6 weeks in pregnancy
for all disease and therapies
center
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Percentage of misidentified samples in a biobank Percentage of collection errors that occur
BioArray News, April 23, 2013
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§ Mixing samples from two individuals (especially common
when collecting family samples at the same time)
§ QA procedures and sample tracking systems allow historic
dissection of mislabeling errors (which can then be corrected)
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Integrated sample processing, analytical and functional quality control is critical for success on a program wide level
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Identity-Theft is the fastest growing crime in America; 9.9 MILLION victims were reported last year, according to a Federal Trade Commission survey! Biobanking is the fastest growing component in translational research; over 9 MILLION samples were collected world wide last year, according to a collection of study reports!
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§ gDNA, WGA, FF DNA
§ total RNA, mRNA, miRNA
§ lysates, serum, plasma
§ fresh frozen, FFPE, preserved
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336 Million people in US In 2017
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126M hospital visits
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885M doctors office visits
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13B diagnostic tests are with <10% for molecular analyses
Imagine on average 5 biosample aliquots for each person that visited the doctor…4.4B samples Imagine the collection of 5 biomaterials each year for 50 years…220B samples Molecular samples will exceed the number of paraffin blocks by several orders of magnitude
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Integrating sample collection, bioprocessing and management with an eye on the molecular central dogma Understanding the power of evolving technologies and developing a sample centric roadmap for future sample use Creation of sample quality control metrics to standardize across all collections Creating a resource that will integrate seamlessly with both industrial and academic collaborative opportunity
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Sample Collection (Clinical Trial) Sample Processing (Biobank) Sample Distribution & Data Mgmt PGx Genotyping (Service Lab) Data Transfer & Analysis
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OLD NEW
For Reserarch Use Only – Not for use in diagnostic procedures
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For Reserarch Use Only – Not for use in diagnostic procedures
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Product Application area Highlights
DMET Plus Solution Available since 2008
genotyping
PharmacoScan Solution Available now
pharma and biorepositories/biobanks
insertion/deletions (INDELs), copy number variations (CNVs) in one run
DMET Plus Solution PharmacoScan Solution
For routine use For higher-throughput screening
24- and 96-sample array plate formats Single sample cartridge format
For Reserarch Use Only – Not for use in diagnostic procedures
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For Reserarch Use Only – Not for use in diagnostic procedures
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For Reserarch Use Only – Not for use in diagnostic procedures
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Sample Collection (Clinical Trial)
Sample Processing & PGx Genotyping (Service Lab)
Sample Storage (Biorepository) Data Transfer & Analysis
(GWAS, HLA, DMET, etc…)
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Past Recent Past Present
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Treatment Patients
Clinical efficacy No clinical efficacy Adverse Event
Bench to Bedside Bedside to Bench Patients Diagnostic Biomarkers
Clinical efficacy Clinical efficacy Clinical efficacy
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For Reserarch Use Only – Not for use in diagnostic procedures
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Tissue Blood for DNA Protocol plan Enrolled patient Programmatic Strategy
Sample Collection Sample/Prep & Biorepository
libraries
Blood for RNA
Data Generation
Data Analysis and Results
Outcomes
biomarkers
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Phase I Phase II Phase III
Inform Discovery
Candidate Genes Drug metabolism, drug targets Primary Discovery GWAS + WES Genetic Marker/ Positive Result YES NO Stratified Trial Enriched for responders Continued Discovery GWAS, targeted genotyping, +/- WES
CLINICAL PROGRAM Biomarker Validation, Mechanism of Action, Novel Biomarkers, New Targets GENETICS Genetic variation explains PK variability Genetic variation Explains variable efficacy Validation: Phase II GWAS “hit” predicts for response in Phase 3
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