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Pharm 202 “Digitally Enabled Genomic Medicine” and Its Role in Cancer Treatment. Phil Bourne [email protected] http://www.sdsc.edu/pb -> Courses -> Pharm 202. Take Home Message. We are undergoing a revolution in our approach to treating disease

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Pharm 202 digitally enabled genomic medicine and its role in cancer treatment l.jpg
Pharm 202“Digitally Enabled Genomic Medicine” and Its Role in Cancer Treatment

Phil Bourne

[email protected]

http://www.sdsc.edu/pb -> Courses -> Pharm 202


Take home message l.jpg
Take Home Message

  • We are undergoing a revolution in our approach to treating disease

  • This has been driven by the human genome project and the technologies that go with it

  • A key element is the integration of information derived from genotype to phenotype

  • Much of this information is now digital rather than analog

  • This is much more than faster ways to develop drugs – it has to do with diagnostic treatments, preventive medicine, personalized medicine

  • Remember the two applications associated with cancer treatment


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Today -

  • Overview of the revolution

  • Drug discovery specifically

  • The much more part as it relates to cancer

    • Improve the outcomes of radiotherapy in treatment of breast and prostate cancer

    • Predictive gene signatures to define treatments for breast cancer


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Approach Today

  • Rather than discuss specific papers of work completed we will take a broader perspective on proposed work on large scale projects that have the potential to impact people’s lives through digitally enabled genomic medicine

  • The grants we have studied are from Genome Canada and should be treated as confidential


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SCIENTIFIC RESEARCH

& DISCOVERY

Anatomy

Migratory

Sensors

Organisms

Physiology

Ventricular

Modeling

Organs

Cell Biology

Electron

Microscopy

Cells

Macromolecules

Biopolymers

Proteomics

Genomics

X-ray

Crystallography

Infrastructure

Technologies

Medicinal

Chemistry

Protein

Docking

Atoms & Molecules

Training

EXAMPLE

UNITS

REPRESENTATIVE

DISCIPLINE

REPRESENTATIVE

TECHNOLOGY

MRI

Heart

Neuron

Structure

Sequence

Protease

Inhibitor


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Digital vs Analog

  • The lower levels of biological complexity have always been digital – the higher levels analog

  • This made it very hard to correlate across biological scales

  • Some good examples of digital phenotypic data exist and it is now being collected in earnest


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Lower Levels – Digital (sort of)

This digital image of cAMP dependant

protein kinase (PKA) depicts years of collective knowledge.

We can only interpret it in this form and the computer is vital


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Higher Levels – The Patient Record

  • 8% of patient records are lost

  • They are mostly paper (analog)

  • They can only be interpreted by humans

  • Errors are rampant

  • There are exceptions – tumor registries, digitized x-rays, clinical trials, the Cockrane library


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Drug Discovery as an Example of this Revolution

  • Requires a higher level of digital enablement

  • Has been accelerated by the genome(s) and associated technologies


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Discovery and Development

  • Discovery includes: Concept, mechanism, assay, screening, hit identification, lead demonstration, lead optimization

  • Discovery also includes in vivo proof of concept in animals and concomitant demonstration of a therapeutic index

  • Development begins when the decision is made to put a molecule into phase I clinical trials


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Discovery and Development

  • The time from conception to approval of a new drug is typically 10-15 years

  • The vast majority of molecules fail along the way

  • The estimated cost to bring to market a successful drug is now $800 million!! (Dimasi, 2000)


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Drug Discovery - Status Today

  • Somewhat digitally enabled (FDA still requires paper submission)

  • Will benefit from emergent technologies

  • Human targets are relatively well defined

  • Process for finding appropriate targets in other organisms is evolving

  • Process for finding leads is under revision (we will see an example of that)


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Drug Discovery Processes Today

Physiological

Hypothesis

Primary Assays

Biochemical

Cellular

Pharmacological

Physiological

Molecular

Biological

Hypothesis

(Genomics)

Initial Hit

Compounds

Screening

+

Sources of Molecules

Natural Products

Synthetic Chemicals

Combichem

Biologicals

Chemical

Hypothesis


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Drug Discovery Processes - II

Hit to Lead

Chemistry

- physical

properties

-in vitro

metabolism

Secondary

Evaluation

- Mechanism

Of Action

- Dose Response

Initial Hit

Compounds

Initial Synthetic

Evaluation

- analytics

- first analogs

First In Vivo

Tests

- PK, efficacy,

toxicity


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Drug Discovery Processes - III

Lead Optimization

Potency

Selectivity

Physical Properties

PK

Metabolism

Oral Bioavailability

Synthetic Ease

Scalability

Pharmacology

Multiple In Vivo Models

Chronic Dosing

Preliminary Tox

Development

Candidate

(and Backups)


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Remains Serendipity

  • Often molecules are discovered/synthesized for one indication and then turn out to be useful for others

    • Tamoxifen (birth control and cancer)

    • Viagra (hypertension and erectile dysfunction)

    • Salvarsan (Sleeping sickness and syphilis)

    • Interferon-a (hairy cell leukemia and Hepatitis C)


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Issues in Drug Discovery

  • Hits and Leads - Is it a “Druggable” target?

  • Resistance

  • Pharmacodynamics and kinetics

  • Delivery - oral and otherwise

  • Metabolism

  • Solubility, toxicity

  • Patentability


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What has changed in identifying targets?In principle we know all the human targets - The “Druggable Genome”


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human genome

Problems with toxicity, specificity, and difficulty in creating potent inhibitors eliminate the first 3 categories...

polysaccharides

nucleic acids

proteins

lipids


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human genome

“druggable genome” = subset of genes which express proteins capable of binding small drug-like molecules

polysaccharides

nucleic acids

proteins

lipids

proteins with binding site


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Relating druggable targets to disease...

Analysis of pharmindustry reveals:

  • Over 400 proteins used as drug targets

  • Sequence analysis of these proteins shows that most targets fall within a few major gene families (GPCRs, kinases, proteases and peptidases)

Fig. 3, Fauman et al.


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Remaining issues

  • Characterization of human proteins is on-going (see each revision from Ensembl)

  • Our ability to locate coding regions is improving

  • Our ability to annotate putative proteins is improving

  • More targets will be identified


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No?

  • Bioinformatics

  • Distant

  • homologs

  • Domain

  • recognition

  • Bioinformatics

  • Alignments

  • Protein-protein

  • interactions

  • Protein-ligand

  • interactions

  • Motif recognition

Automation

Better

sources

  • Automation

  • Bioinformatics

  • Empirical

  • rules

Software integration

Decision Support

MAD Phasing Automated

fitting

Anticipated Developments

The Structural Genomics Pipeline

(X-ray Crystallography)

Basic Steps

  • Crystallomics

  • Isolation,

  • Expression,

  • Purification,

  • Crystallization

Target

Selection

Data

Collection

Structure

Solution

Structure

Refinement

Functional

Annotation

Publish


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From Structural Genomix

  • FAST™ is a proprietary lead generation technology developed by SGX for identification of novel, potent and selective small molecule inhibitors of drug targets within a rapid six-month timeframe. The FAST™ process involves crystallographic screening of lead-like drug fragments followed by structure-guided elaboration of the fragments by parallel chemical synthesis, guided by proprietary computational tools. Iterative determination of crystal structures for multiple target/compound complexes in parallel with assays, computational design and synthesis results in optimized leads with high binding affinities and low molecular weights. The combinatorial nature of FAST™ provides access to expansive chemical diversity in the order of 160 million compounds, while requiring only a small number of compounds to be synthesized and screened. Thus the FAST™ approach generates novel and potent lead compounds within months and with efficient deployment of chemistry resources.


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Summary

  • Need information flow from genotype to phenotype and back

  • Digital enablement provides that

  • The human genome and the associated technologies has accelerated this process dramatically

  • Example – human genome provides more targets

  • Example – structural genomics leads to faster identification of leads

  • Lets consider two examples related to cancer that illustrate this more specifically….


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