big data and analytic strategies simplifying clinical research, making trials cost-effective
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Candida Fratazzi MD President
Boston Biotech Clinical Research, LLC Simplifying Clinical Research
www.bostonclinicalresearch.com
Big data and analy>c strategies:
Simplifying Clinical Research,
making Trials Cost-‐Effec>ve
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Henry Ford devised a manufacturing system of mass produc>on, using
specialized machinery and standardized products
ü Ford changed the way we made cars – and transformed work itself
Big Data not only refers to very large data sets and the tools and procedures
used to manipulate and analyze them, but also to a computa>onal turn in
thought and research (Burkholder 1992)
ü Big Data creates a radical shiO in how we think about research
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Presenta>on’s Map
Big Data challenge and
opportunity
Personalized medicine
Innovation in clinical
research Algorithm
development
Better disease treatments for a cost-efficient healthcare
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Data complexity
data source
Variety
data size
Volume
speed of change
Velocity
Big Data Technology Challenge
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• Modern medicine collects huge amounts of informa>on about pa>ents through imaging technology (CAT scans, MRI), gene>c analysis (DNA microarrays), and other forms of diagnos>c equipment
• Applying data mining to data sets for large numbers of pa>ents, medical researchers are gaining fundamental insights into the gene>c and environmental causes of diseases, and crea>ng more effec>ve means of diagnosis
B ig Data Opportuni>es
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Personalized Medicine
“……..personalized medicine is a sort of shorthand used to represent the
logical next steps in progression of medical science toward greater
mechanis>c understanding of health, disease, and treatment.”
Janet Woodcock
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From Blockbusters to Personalized Medicine • The biggest challenges for the biotechnology and pharmaceu>cal
companies is to develop and deliver drugs that fit the individual pa>ent’s biology and pathophysiology
• Change from blockbuster medicine to personalized medicine will influence the way that drugs are developed, and prescribed in the future
• Personalized medicine is a stepwise process to stra>fy pa>ents into different molecular/ biological subgroups
• Cancer Medicine is expec>ng to deliver in 10–15 years many more drugs using CDx
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Right drug, Right pa>ent, Right dose
Adapted from Vikas Kumar, The role of pharmacogenomics in drug development
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Lack of Efficacy and…Side Effects
ü 20-‐75% of pa>ents do not receive effec>ve treatment
ü >100,000 deaths per year from adverse drug reac>ons in the US only
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Rheumatoid Arthri>s case study
Heterogeneity based on response To Enbrel
B Cell-driven
TNF-driven IL-6-driven
T cell-driven
Comorbidities
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Right drug, Right pa>ent, Right dose
Personalized Medicine requires Innova8on in Clinical Research to:
• Reduce clinical development and CRO cost
• Improve pa>ent recruitment and accelerate trial execu>on
• Reduce clinical failure and generate reproducible data
To create evidence-‐based data driven trials
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S C I O
Strategic Clinical Innova>on Organiza>on
a new class of service
B o s t o n B i o t e c h C l i n i c a l R e s e a r c h
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Finding the Meaning in “ Meaningful Use ” Trial Protocol Variables
1. Product (Drug, device, or diagnos>c) MOA 2. Disease pathology 3. Unmet medical needs 4. Disease incidence and geography 5. Compe>>on and products in development 6. Select subset pa>ent popula>on likely to show a significant improvement
considering MOA 7. Iden>fy clinically meaningful endpoint/s 8. Control for co-‐morbidi>es 9. Consider selec>ng an ac>ve control to assist in pharmaco-‐economic support for
reimbursement 10. Select meaningful outcomes and define the clinically significant minimal
difference
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Discovery / Pre-‐Clinical
CRO
Innova>on in Cl inical Research
SCIO PK/PD
Diagnostics Biomarkers
Drug-Target Design
Endpoints
Patients’ stratification
Safety
Regulators Disease staging
Study protocol
Market analysis
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Cytokine Signaling Pathways relevant to Early RA
CYTOPLASM NUCLEUS
Kinases
Kinases
p38
JNK ERK
Syk
IKK
NFκB
JAK JAK
STAT
STAT
STAT STAT
Gene transcrip>on
PI3K
PI3K PI3K
Lipid messengers
Second messengers
MAPK signalling cascade
SYK, (& BTK) signalling cascade
NFKB signalling cascade
JAK signalling cascade
PI3K
BTK
e.g. MKK3, MKK6
Adapted from Mavers M, et al. Curr Rheum Rep 2009; 11: 378–385; and Rommel C, et al. Nat Rev Immunol 2007; 7: 191–201.
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Therapeu>c Indica>on Selec>on for POC
Ankylosing spondyli8s (AS) Serum MMP-‐3
IL-‐6 VEGF CRP
Crohn’s disease (CD) An8-‐S. Cerevisiae Ab
Perinuclear an8neutrophil cytoplasmic Abs Laminaribioside Chitobioside
Juvenile idiopathic arthri8s (JIA)
IgM RF IgA RF
An8cyclic citrullinated pep8de
Abs
SLE CD27 high plasma cells
Soluble IL-‐2 receptor (CD25) Soluble thrombomodulin Soluble TNF receptor Soluble VCAM-‐1 Type I INF-‐a, IFB-‐b
An8-‐dsDNA BLyS
CD19+ B cells CD40 ligand = lymphocytes IL-‐6, 10, 12, p40, 12, 16, 18
Rheumatoid arthri8s(RA)
An8nuclear Ab Rheumatoid factor
CRP Erythrocyte
sedimenta8on rateHLA-‐B27
Ulcera8ve coli8s (UC) An8-‐S. Cerevisiae Ab
Perinuclear an8neutrophil cytoplasmic Abs Laminaribioside Chitobioside
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Dis>l l ing Meaning from Big Data
Approximate ly 4000 New Tests / next 10 years
An a l go r i thm to d i s8 l l a coherent p i c tu re o f d i sease f rom a w ide range o f d i spa ra te da ta
Metabolomics
Proteomics Genomics Epigene>cs Microbiome Imaging
ü Blood ü Urine ü Fluids ü Tissue
ü RNA ü Protein ü Metabolites ü Images
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There is No App for Clinical Research INNOVATION Tech solu>ons alone are not enough !!
• Applying new technology to old development models is not good enough
• Use of technology alone cannot innovate clinical research
• Technology advancement is key to improve Variety, Volume and Velocity management
• Clinical Research INNOVATION requires algorithm/s that dis>lls meanings from big data
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Finding the meaning: the Algorithm
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The Ul>mate Goal
• Simplifying Clinical Research meets the requirements of investors, partners and regulators
• Strategizing Clinical Plan accelerates value crea>on from phase I and II of clinical trials
• Genera8ng Evidence-‐based Medicine reduces clinical risk and maximizing the chance of a successful outcome
• Design Focused Trials results in cost-‐effec>ve clinical trials
• Develop Algorithm/s to integrate Big Data for decision making
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Working on Algorithms Development
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Algorithms for Cl inical Research
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Simplifying Clinical Research affects Healthcare
• Personalized medicine is poised to transform healthcare
• New diagnos>c and prognos>c tools will increase our ability to predict drug therapy outcomes
• Expanded use of biomarkers will result in targeted drug development
Treatments developed for Personalized Medicine improve Healthcare Quality and make Healthcare Cost-‐effec>ve
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