This document discusses the drug discovery process from target identification through FDA approval. It describes methods used for target identification such as genomics, bioinformatics, and proteomics. The stages of lead identification through high-throughput screening and structure-based drug design are outlined. Key aspects of lead optimization like characterizing potency, efficacy, pharmacokinetics, and toxicity are summarized. Details are provided on preclinical and clinical trial phases from Phase 0 through Phase IV post-marketing surveillance. Factors contributing to the declining drug approval rate like increased safety demands are noted. The high costs and failure rates associated with drug development are highlighted.
1. Prof. Thanh N. Truong
Department of Chemistry, University of Utah
Institute for Computational Science and Technology, Vietnam
Astonis LLC
2. Top 10 Pharmaceutical Company Sale Figures
•2004 (billions USD)
•2005 (billions USD)
•2006 (billions USD)
Johnson & Johnson
47.4
Pfizer
44.2
Pfizer
45.1
Pfizer
45.2
GlaxoSmithKline
34.0
GlaxoSmithKline
37.0
GlaxoSmithKline
39.0
Aventis-Sanofi
34.0
Aventis-Sanofi
35.6
Novartis
28.2
AstraZeneca
24.0
Novartis
28.9
Hoffman LaRoche
24.5
Johnson & Johnson
22.3
Hoffman LaRoche
26.6
Merck
22.9
Merck
21.9
AstraZeneca
25.7
AstraZeneca
21.4
Novartis
20.3
Johnson & Johnson
23.3
Aventis-Sanofi
20.4
Abbott Labs
19.7
Merck
22.6
Abbott Labs
19.7
Hoffman LaRoche
16.6
Wyeth
15.7
Bristol-Myers Squibb 15.3
Eli Lilly
14.8
Bristol-Myers Squibb 19.4
3. R&D Spending and Return on Investments
Research based pharmaceutical companies, on average, spend
about 20% of their sales on research and development (R&D).
This percentage is significantly higher than in most other
industries, including electronics, aerospace, automobiles, and
computers.
Since 1980 US pharmaceutical companies have practically
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 90s
Innovation Deficit
Jurgen Drews, Hoffmann-LaRoche
4. 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 40 in the
80s, to 70 in the 90s
Lead to the prolonged duration of the drug development
process.
o In the 60s, total development time was 8.1 yrs
o In the 70s, total development time was 11.8 yrs
o In the 80s, total development time was 14.2 yrs
o In the 90s, total development time was 14.9 yrs
o Currently, total development time is ~16 yrs
“low hanging fruit” have been picked.
5. 16 years and about 880 Millions USD for a New Drug
Time Line
6. Return on Investment
About 75% of this cost ($660 million) is attributable
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!
7. The Drug Discovery Process
Drug Target
Identification
Target
Validation
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
8. Drug Target
Identification
Target
Validation
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
The identification of new, clinically relevant, molecular targets is of
utmost importance to the discovery of innovative drugs.
Current therapy is based upon less than 500 molecular 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 44:291-300 2000; Biopolymers 60:206-211
2001)
9. 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
11. 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 complexity of
biological systems lies at the level of the proteins, and that
genomics alone will not suffice to understand these systems.
12. Bio-informatics
Bioinformatics methods are used to transform the raw
sequence into meaningful information (eg. genes and their
encoded proteins) and to compare whole genomes (disease vs. not).
Sequencing of microbial genomes will enable the identification
of novel drug targets, especially when comparing to the human
genome.
In silico identification of novel drug targets is now feasible by
systematically searching for paralogs (related proteins 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 genes/proteins
associated with pathogenism.
13. Proteomics
Proteomics is the systematic high-throughput separation and
characterization of proteins within biological systems.
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
14. Drug Target
Identification
Target
Validation
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
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 knock-in
animal models, small molecule inhibitors/agonists/antagonists,
antisense nucleic acid constructs, ribozymes, and neutralizing
antibodies.
Since strong interactions between a protein and its ligand are
characterized by a high degree of complementarities in their shapes
and charge distributions, knowledge of the protein three dimensional
structure will enable the prediction of “druggability” of the protein.
15. Drug Target
Identification
Target
Validation
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
Organic compounds are identified which interact with the target protein and
modulate its activity by using random (screening) or rational (design) approaches.
High-throughput Screening
Natural product and synthetic compound libraries with millions of
compounds are screened using a test assay.
In theory generating the entire ‘chemical space’ for drug molecules and
testing them would be an elegant approach to drug discovery.
In practice, this isn’t feasible. -- Drug Discovery Today 5:2-4 2000
Structure Based Drug Design
Three dimensional structures of compounds from virtual or physically
existing libraries are docked into binding sites of target proteins with
known or predicted structure.
Scoring functions evaluate the steric and electrostatic complementarity
between compounds and the target protein.
The highest ranked compounds are then suggested for biological testing. -Drug Discovery Today 7:64-70 2002
16. Other criteria for leads
Pharmacodynamic properties - efficacy, potency, selectivity
Physiochemical properties - water solubility, chemical stability,
Lipinski’s “rule-of-five”.
Pharmacokinetic properties - metabolic stability and
toxological aspects.
Chemical optimization potential - ease of chemical
synthesisand derivatization.
Patentability
17. Drug Target
Identification
Target
Validation
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
Molecules are chemically modified and subsequently
characterized in order to obtain compounds with suitable
properties to become a drug.
Leads are characterized with respect to pharmacodynamic
properties such as efficacy and potency in vitro and in vivo,
physiochemical properties, pharmacokinetic properties, and
toxicological aspects.
Once compounds with desirable in vitro profiles have been
identified, these are characterized using in vivo models.
18. Charaterizing Leads
Potency refers to the amount of drug required for its specific effect to
occur
Efficacy measures the maximum strength of the effect itself, at
saturating drug concentrations.
Pharmacokinetics - determining the fate of xenobiotics. - “what the
body does to the drug.”
Pharmacodynamics - determining the biochemical and physiological
effects of drugs, the mechanism of drug action, and the relationship
between drug concentration and effect. - “what the drug does to the
body”
Lead optimization requires the simultaneous optimization 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 from
molecular modeling, quantitative structure-activity relationships, and from
structural biology (structure-based drug design)
20. 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.
21. Five Phases of Clinical Trials
Phase 0 - First-in-human trials -- human micro-dosing studies
and are designed to speed up the development of promising
drugs by establishing very early on whether the drug 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, pharmacokinetics,
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.
23. 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 definitive
assessment of the efficacy of the new therapy, in comparison
with standard therapy. Side effects are also monitored. -it is
typically expected that there be at least two successful phase III
clinical trials to obtain approval from the FDA.
Once a drug has proven acceptable, the trial results are combined into
a large document which includes a comprehensive description of
manufacturing procedures, formulation details, shelf life, etc. This
document is submitted to the FDA for review.
24. 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 effects over a large
patient population and timescale than was possible during clinical
trials.
25. Vioxx Saga: multi-billion-dollar share of the arthritis and pain-relief market
USA Today 10/12/2004: How did Vioxx debacle happen?
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.
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 threeyear, 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.
26. Structure-based Computer-Aided Drug Design
Drug Target
Identification
Target
Validation
Shorten development
time to Lead
Identification
Reduce cost
Past Successes
1.
2.
3.
HIV protease inhibitor
amprenavir (Agenerase)
from Vertex & GSK (Kim et
al. 1995)
HIV: nelfinavir (Viracept) by
Pfizer (& Agouron) (Greer et
al. 1994)
Influenza neuraminidase
inhibitor zanamivir
(Relenza) by GSK
(Schindler 2000)
Lead
Identification
Lead
Optimization
Pre-clinical &
Clinical
Development
FDA Review
27. Science Community Laboratory
Integrate science research in society
Engage citizen scientists to participate in drug discovery
Learn how structure-based drug design work while help
fighting neglected diseases
Join SciCoLab Now!