Implementation of Genetic Analysis in Comprehensive

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Implementation of Genetic Analysis in Comprehensive Biobank Workflows for Basic Science, Clinical Research and Precision Medicine ApplicationsDr. Andrew BrooksCOO, RUCDR Infinite BiologicsRutgers University


We now use biological samples to accomplish important activities to create better therapies:- Research and development- Biomarker discovery- Targeted clinical trials- Rational drug development- Creation of new diagnostics

The future of biosample collection and analysis promises a change in how we think about healthcare:- Integrative wellness monitoring- Complete health prediction based on

genetics and environment- Whole genome sequencing prior as

early as 6 weeks in pregnancy- Comprehensive molecular monitoring

for all disease and therapies- Point of care testing…every doctors

office, clinic, hospital, and medical center

Planning for the future…

A banked sample is proactively acquired for future testing or analysisA banked sample is often sent to multiple different recipientsA banked sample should never be depleted

What is the difference between a “Stored” sample and a “Biobank” Sample?

Biological Storage/Banking Defined


Repository Management Operations:Enterprise Level Integration


COLLECTION STORAGE

EXTRACTION

Adverse Sample Quality Events


Where do the errors come from?

2%98%

Percentage of misidentified samples in a biobank

Percentage of collection errors that occur outside of the biobank

Dr.AndyBrooksin“Q&A:RUCDR'sAndyBrooksontheChallengesFacingBiorepositoriesandtheRiseofBiobankArrays”BioArrayNews,April23,2013


Samples just keep on being collected…what exactly is being analyzed?

Sample Collection – No Control§ Collection errors (98% of biorepository errors)§ Variability in sampling and processing§ Lack of standardization

Sample Sources – Process Control§ Fresh Tissue/Blood§ Fresh Frozen Tissue/Blood§ Formalin Fixed Paraffin Embedded § Cell Lines (lymphoblasts, fibroblasts)§ Pluripotent Cells – iPSC’s


Sources of errors…

Sample identity errors are often revealed by lack of Mendelian relationship between samples.

- Non-paternity, non-maternity (adopted)

- Mislabeling in field (most common error)

§ Mixing samples from two individuals (especially common when collecting family samples at the same time)

Repository errors§ QA procedures and sample tracking systems allow historic

dissection of mislabeling errors (which can then be corrected)

o Photographing blood tubes/ saving blood sample

o No manual transcription

o Capture data on all processing and QA/QC stepswww.brookslifesciences.com 8

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Integrated sample processing, analytical and functional quality control is critical for success on a program wide level

IntegratedProcesses:QualificationforDownstreamAnalysis

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Identity Theft: Financial vs. Biological

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!


Analytical Quality Control:Moving towards standardization

Volume§ Contact vs. Non-contact

Concentration§ Sample heterogeneity

Purity/Fidelity§ Establishing application dependent metrics

Annotation§ Critical for comparative analysis

Sample Retesting§ How often and how to interpret?


Functional Quality Control:Moving towards standardization

DNA§ gDNA, WGA, FF DNA

RNA§ total RNA, mRNA, miRNA

Protein§ lysates, serum, plasma

Tissue§ fresh frozen, FFPE, preserved

Functional Analysis Over Timewww.brookslifesciences.com 12

Nucleic Acid Quality Control

Analytical QC§ Concentration§ Purity§ Yield§ Volume

Functional QC§ Contamination§ Performance§ Fingerprint§ Subject screening


Advances in Functional QCRUIDTM QC Panel

96 SNPtypeTM Assays§ Highly polymorphic§ Critical performance SNPs§ 80% cover Affymetrix and Illumina§ Gender, Ethnicity, Parentage§ FLEXIBLE§ Inexpensive

Integrated Real Time Database§ Profile comparison§ Sample comparison§ Gender/Ethnicity calls§ Sample performance§ LIMS Integration


The way we do research and the standard of care is changing

336 Million people in USIn 2017§ 126M hospital visits§ 885M doctors office visits§ 13B diagnostic tests are with

<10% for molecular analysesImagine on average 5 biosamplealiquots for each person that visited the doctor…4.4B samplesImagine the collection of 5 biomaterials each year for 50 years…220B samplesMolecular samples will exceed the number of paraffin blocks by several orders of magnitude

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Science and Technology: Driving Innovation

Integrating sample collection, bioprocessing and management with an eye on the molecular central dogmaUnderstanding the power of evolving technologies and developing a sample centric roadmap for future sample useCreation of sample quality control metrics to standardize across all collectionsCreating a resource that will integrate seamlessly with both industrial and academic collaborative opportunity

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The Promise of Precision Medicine

Clinical PGx – Precision Medicine


Sample Collection

(Clinical Trial)

Sample Processing(Biobank)

Sample Distribution &

Data Mgmt

PGxGenotyping

(Service Lab)

Data Transfer & Analysis

Total Time to Data: ~6-9 mosFTE Allotment: Cost: ~$1750

Workflow – Current State


OLD

NEW

Integrated Biobank & Genetics Workflow

For Reserarch Use Only – Not for use in diagnostic procedureswww.brookslifesciences.com 20

Pharmacogenomics Solutions

Individual Assays§ Costly§ Incomplete§ Subject to validation

Affymetrix DMET§ Less expansive content§ Largely manual process/array development

Affymetrix PharmacoScan§ Expansive content§ Multiple uses for biobank applications§ Completely automated


Advances in PharmacogenomicsProduct Application area Highlights

DMET Plus SolutionAvailable since 2008 • Routine low-volume

genotyping

• 1,936 ADME markers in 231 genes• Star allele translation for key genes• Single sample approach

PharmacoScan SolutionAvailable now

• Precision PGx profiling• Larger-scale programs• Preemptive screening for healthcare,

pharma and biorepositories/biobanks

• 4,627 ADME markers in 1,191 genes• Star allele translation for key genes• Content from CPIC, PharmaGKB & more• Single-nucleotide polymorphisms (SNPs),

insertion/deletions (INDELs), copy number variations (CNVs) in one run

• 24 or 96 batch assay in affordable plate format

DMET Plus Solution PharmacoScan SolutionFor routine use For higher-throughput screening

24- and 96-sample array plate formatsSingle sample cartridge format

Pharmacogenetics Redefined…


Chemistry Principles


Fully Automated Workflow


Total Time to Data: Real-timeFTE Allotment:Cost: ~$200

Sample Collection

(Clinical Trial)

Sample Processing & PGx

Genotyping(Service Lab)

Sample Storage

(Biorepository)

Data Transfer & Analysis (GWAS, HLA, DMET, etc…)

Biobank Integration

Workflow – Ideal State


• Data Quality– Process combined with functional QC– Enhanced subject stratification– Critical information for drug/therapy development

• Types of Data– Integrate “screening” with “deep analysis”

• Time to Data– Reduced by months and allows for rapid analysis real time or

immediately following consent review• Fiscal Advantages

– Up to 50% reduction in operating costs

Advantages of Biobank & Genetic Analysis Integration


•4

Past

RecentPast

Present

Past, Recent Past, Present

+

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Overall Advantages of Biobanking & PGx Genetic Analysis Integration

Data Quality§ Process combined with functional QC§ Critical information for drug development and subject stratification

Time to Data§ Reduced by months which also leads to additional cost reductions

Fiscal Advantages§ Up to 50% reduction in operating costs


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Treatment

Patients

Clinical efficacy

No clinical efficacy

Adverse Event

Benc

htoB

edsid

e

Beds

ideto

Benc

h

Patients

Diagnostic Biomarkers

Clinical efficacy

Clinical efficacy

Clinical efficacy

Clinical PGx – Precision Medicine


A Validated PGx Solution: PMRA


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Tissue

Blood for DNA

Protocolplan

Enrolled patient

ProgrammaticStrategy

Sample CollectionSample/Prep &Biorepository

• Tissue–DNA• Tissue–RNA• Blood --DNA• Blood – RNA• Associated

librariesBlood for RNA

Data Generation

• Tissue WES• Tissue RNAseq• Blood WGS• Blood RNAseq• Blood genotyping

Data Analysisand Results

Outcomes• Real-time program strategy• Treatment combinations• Treatment mechanisms• Understanding value of novel

biomarkers

Molecular Profiling Workflow


Phase I Phase II Phase III

Inform Discovery

Candidate GenesDrug metabolism,drug targets

Primary DiscoveryGWAS + WES

Genetic Marker/ Positive Result

YES

NO

Stratified Trial Enriched for responders

Continued Discovery GWAS, targeted genotyping, +/- WES

CLINICALPROGRAM 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

“New” Routine Genetic Research in Clinical Trials


Questions…


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Implementation of Genetic Analysis in Comprehensive