Introduction to the drug discovery process

Prof. Thanh N. TruongDepartment of Chemistry, University of Utah

Institute for Computational Science and Technology, Vietnam

Astonis LLC

Top 10 Pharmaceutical Company Sale Figures

•2004 (billions USD)

Johnson & Johnson 47.4

Pfizer 45.2

GlaxoSmithKline 39.0

Novartis 28.2

Hoffman LaRoche 24.5

Merck 22.9

AstraZeneca 21.4

Aventis-Sanofi 20.4

Abbott Labs 19.7

Bristol-Myers Squibb 19.4


Pfizer 44.2


Aventis-Sanofi 34.0

AstraZeneca 24.0


Merck 21.9

Novartis 20.3

Abbott Labs 19.7


Bristol-Myers Squibb 15.3


Pfizer 45.1


Aventis-Sanofi 35.6

Novartis 28.9


AstraZeneca 25.7


Merck 22.6

Wyeth 15.7

Eli Lilly 14.8

R&D Spending and Return on Investments

� Research based pharmaceutical companies, on average , spend about 20% of their sales on research and developmen t (R&D).

� This percentage is significantly higher than in mos t other industries, including electronics, aerospace, autom obiles, and computers.

� Since 1980 US pharmaceutical companies have practic ally doubled spending on R&D every 5 yrs.

� Despite these enormous expenditures, there has been a steady decline in the number of drugs introduced each year into human therapy.

� 70-100 in the 60s

� 60-70 in the 70s

� ~50 in the 80s

� ~40 in the 90sInnovation Deficit

Jurgen Drews, Hoffmann-LaRoche

Reasons for Innovation Deficit

� Increased drug safety demands by FDA

� the average number of clinical trials per new drug application (NDA) increased from 30 in the 70s to 4 0 in the 80s, to 70 in the 90s

� Lead to the prolonged duration of the drug developm ent process.

o In the 60s, total development time was 8.1 yrs




o Currently, total development time is ~16 yrs

� “low hanging fruit” have been picked.

16 years and about 880 Millions USD for a New Drug

Time Line

Return on Investment

� About 75% of this cost ($660 million) is attributab le to failure during the development.

� 90% of all drug development candidates fail to make it to market.

Methods that enhance the drug discovery process and reduce failure rates are highly desirable!

The Drug Discovery Process

Drug Target Identification

Target Validation

Lead Identification

LeadOptimization

Pre-clinical &Clinical

DevelopmentFDA Review

� Current therapy is based upon less than 500 molecul ar targets of about 10000 possible targets

� 45% of which are G-protein coupled receptors

� 28% are enzymes

� 11% are hormones and factors

� 5% ion channels

� 2% nuclear receptors

� Besides classical methods of cellular and molecular biology, new techniques of target identification are becoming increasingly important. These include:

� genomics (Biotechniques 31: 626-630 2001)

� bioinformatics (Drug Discovery Today 7:315-323 2002 )

� proteomics (J. Pharmacol. Toxicol. Methods 44:291-3 00 2000; Biopolymers 60:206-211 2001)


Target Validation

Lead Identification

LeadOptimization



The identification of new, clinically relevant, mol ecular targets is of utmost importance to the discovery of innovative dr ugs.

Genomics

� Genetic information is contained with DNA (deoxyribonucleic acid) and RNA (ribonucleic acids)

� Each plant, animal or bacteria carries its entire genetic code inside almost every one of its cells

� Genomics is the discipline that aims to decipher and understand the entire genetic information content of an organism

Bio-informatics

25,000

metabolite

Genomics Facts

� Around 99% of our genes have counterparts in mice

� Our genetic overlap with chimpanzees is about 97.5%

� The genetic difference between one person and another is less than 0.1 %

� But because only a few regions of DNA actively encode life functions, the real difference between one person and another is only 0.0003 %

It is becoming increasingly evident that the comple xity of biological systems lies at the level of the protein s, and that genomics alone will not suffice to understand these systems.

Bio-informatics

� Sequencing of microbial genomes will enable the ide ntification of novel drug targets, especially when comparing to the human genome.

� In silico identification of novel drug targets is now feasibl e by systematically searching for paralogs (related prote ins within an organism) of known drug targets (eg. may be able to modify an existing drug to bind to the paralog).

� Can compare the entire genome of pathogenic and nonpathogenic strains of a microbe and identify gen es/proteins associated with pathogenism .

Bioinformatics methods are used to transform the ra wsequence into meaningful information (eg. genes and theirencoded proteins) and to compare whole genomes (dis ease vs. not).

Proteomics

� Target identification with proteomics is performed by comparing the protein expression levels in normal and diseased tissues.

� Using gene expression microarrays and gene chip technologies, a single device can be used to evaluate and compare the expression of up to 20000 genes of healthy and diseased individuals at once. --Trends Biotechnology 19:412-415 2001

Proteomics is the systematic high-throughput separa tion and characterization of proteins within biological syst ems.

� Involves demonstrating the relevance of the target protein in a disease process/pathogenicity and ideally requires both gain and loss of function studies.

� This is accomplished primarily with knock-out or kn ock-in animal models, small molecule inhibitors/agonists/a ntagonists, antisense nucleic acid constructs, ribozymes, and n eutralizing antibodies.


Target Validation

Lead Identification

LeadOptimization



Since strong interactions between a protein and its ligand arecharacterized by a high degree of complementarities in their shapes and charge distributions, knowledge of the protein three dimensional structure will enable the prediction of “druggabilit y” of the protein.

� High-throughput Screening

� Natural product and synthetic compound libraries wi th millions of compounds are screened using a test assay.

� In theory generating the entire ‘chemical space’ fo r drug molecules and testing them would be an elegant approach to drug d iscovery.

� In practice, this isn’t feasible. -- Drug Discovery Today 5:2-4 2000

� Structure Based Drug Design

� Three dimensional structures of compounds from virt ual or physically existing libraries are docked into binding sites of target proteins with known or predicted structure.

� Scoring functions evaluate the steric and electrost atic complementarity between compounds and the target protein.

� The highest ranked compounds are then suggested for biological testing. --Drug Discovery Today 7:64-70 2002


Target Validation

Lead Identification

LeadOptimization



Organic compounds are identified which interact wit h the target protein and modulate its activity by using random (screening) o r rational (design) approaches.

Other criteria for leads

� Pharmacodynamic properties - efficacy, potency, sele ctivity

� Physiochemical properties - water solubility, chemic al stability, Lipinski’s “rule-of-five”.

� Pharmacokinetic properties - metabolic stability and toxological aspects.

� Chemical optimization potential - ease of chemical synthesisand derivatization.

� Patentability

� Molecules are chemically modified and subsequently characterized in order to obtain compounds with sui table properties to become a drug.

� Leads are characterized with respect to pharmacodyn amic properties such as efficacy and potency in vitro and in vivo, physiochemical properties, pharmacokinetic properti es, and toxicological aspects.

� Once compounds with desirable in vitro profiles have been identified, these are characterized using in vivo models.


Target Validation

Lead Identification

LeadOptimization



Charaterizing Leads

� Potency refers to the amount of drug required for its speci fic effect to occur

� Efficacy measures the maximum strength of the effect itself, at saturating drug concentrations.

� Pharmacokinetics - determining the fate of xenobioti cs. - “what the body does to the drug.”

� Pharmacodynamics - determining the biochemical and p hysiological effects of drugs, the mechanism of drug action, and the relationship between drug concentration and effect. - “what the dr ug does to the body”

Lead optimization requires the simultaneous optimizat ion of multiple parameters and is thus a time consuming and costly step. It is often the tightest bottleneck in drug discovery.

Hints on how to modify a lead compound can originate frommolecular modeling, quantitative structure-activity relationships, and from structural biology (structure-based drug design)

� Wide ranging dosages of the compounds are introduced to the cell line or animal in order to obtain preliminary efficacy and pharmacokinetic information.


Target Validation

Lead Identification

LeadOptimization



Preclinical studies involve in vitro studies and trials on animal populations.

Five NIH clinical trial types

� Treatment trials : test experimental treatments or a new combination of drugs.

� Prevention trials : look for ways to prevent a disease or prevent it from returning.

� Diagnostic trials : find better tests or procedures for diagnosing a disease.

� Screening trials : test methods of detecting diseases.

� Quality of Life trials : explore ways to improve comfort and quality of life for individuals with a chronic illness.

Five Phases of Clinical Trials

� Phase 0 - First-in-human trials -- human micro-dosing studies and are designed to speed up the development of pro mising drugs by establishing very early on whether the dru g behaves in human subjects as was expected from preclinical studies.

� Phase I - a small group of healthy volunteers (20-80) are selected to assess the safety, tolerability, pharma cokinetics, and pharmacodynamics of a therapy.

� Single Ascending Dose (SAD) studies

� Multiple Ascending Dose (MAD) studies

� Food effect- designed to investigate any differences in absorption caused by eating before the dose is given.

80% of drugs fail the Phase I clinical trial!

On the way to FDA review

� Phase II - performed on larger groups (20-300) and are designed to assess the activity of the therapy, and continue Phase I safety assessments.

� Phase III - randomized controlled trials on large patient groups (hundreds to thousands) aimed at being the d efinitive assessment of the efficacy of the new therapy, in c omparison with standard therapy. Side effects are also monito red. -it is typically expected that there be at least two succe ssful phase III clinical trials to obtain approval from the FDA.

Once a drug has proven acceptable, the trial result s are combined into a large document which includes a comprehensive des cription of manufacturing procedures, formulation details, shel f life, etc. This document is submitted to the FDA for review.

Post Marketing Surveillance Trial

� Phase IV - post-launch safety monitoring and ongoing technical support of a drug.

� may be mandated or initiated by the pharmaceutical company.

� designed to detect rare or long term adverse effect s over a large patient population and timescale than was possible during clinical trials.

Vioxx Saga: multi-billion-dollar share of the arthritis and pain-relief market

May 1999: FDA approves Vioxx.

March 2000: Merck reveals that a new study found Vioxx patients had double the rate of serious cardiovascular problems than those on naproxen, an older nonsteroidal anti-inflammatory drug, or NSAID.

November 2000: The New England Journal of Medicine publishes the study, called VIGOR.

February 2001: An advisory panel recommends the FDA require a label warning of the possible link to cardiovascular problems.

September 2001: The FDA warns Merck to stop misleading doctors about Vioxx's effect on the cardiovascular system.

April 2002: The FDA tells Merck to add information about cardiovascular risk to Vioxx's label.

Aug. 25, 2004: An FDA researcher presents results of a database analysis of 1.4 million patients; it concludes that Vioxx users are more likely to suffer a heart attack or sudden cardiac death than those taking Celebrex or an older NSAID.

Sept. 23, 2004: Merck says it learned this day that patients taking Vioxx in a study were twice as likely to suffer a heart attack or stroke as those on placebo.

Sept. 30, 2004: Merck withdraws Vioxx from the U.S. and the more than 80 other countries in which it was marketed.

USA Today 10/12/2004: How did Vioxx debacle happen ?

February 2001 : Merck tried to convince an FDA advisory committee that Vioxx be allowed to drop the digestive tract warning. But the committee couldn't ignore the cardiovascular findings.

September 2001: The FDA ordered the company to send doctors a letter "to correct false or misleading impressions and information" about Vioxx's effect on the cardiovascular system.

April 2002: the FDA followed its advisory panel's recommendation and required that Merck note a possible link to heart attacks and strokes on Vioxx's label.

Merck was spending more than $100 million a year in direct-to-consumer advertising — another activity regulated by the FDA and a critical mechanism in building the 'blockbuster' status of a drug."

Aug. 2004: the company fired off a press release refuting Graham's study. "Merck stands behind the efficacy, overall safety and cardiovascular safety of Vioxx,"

Sept. 2004 : Merck confronted unfavorable findings that it could not explain away. Merck had sponsored a three-year, 2,600-patient randomized trial to see whether Vioxx, like Celebrex, could claim that it protects against the recurrence of colon polyps, which can become cancerous.

Structure-based Computer-Aided Drug Design


Target Validation

Lead Identification

LeadOptimization



� Shorten development time to Lead Identification

� Reduce cost

Past Successes1. HIV protease inhibitor

amprenavir (Agenerase) from Vertex & GSK (Kim et al. 1995)

2. HIV: nelfinavir (Viracept) by Pfizer (& Agouron) (Greer et al. 1994)

3. Influenza neuraminidase inhibitor zanamivir (Relenza) by GSK (Schindler 2000)

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� Engage citizen scientists to participate in drug discovery

� Learn how structure-based drug design work while help fighting neglected diseases

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Education

Introduction to the drug discovery process