Informatics and Drug Discovery. Peter Goodfellow. 20 th Century Health Achievements. Vaccination Control of infectious diseases Decline in deaths from coronary heart disease and stroke Family planning Healthier mothers and babies Fluoridation of drinking water
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Source: CDC MMWR April 02, 1999 / 48(12);241-243 http://www.cdc.gov/mmwr/preview/mmwrhtml/00056796.htm
Deaths per 100 person-years
Therapy with a PI (% of patient-days)
Use of protease inhibitors
Palella et al. N Engl J Med 1998
Output of New Molecular Entities
Index (% of 1994 output)
Source: CMR International
The Drug Discovery Process
The aim is to translate new information into new therapies
1 Drug Molecule
10,000 Drug Candidates
Valid Biomedical Hypothesis?
1 Drug Launch
Side effect profile
Trial sites and investigators
10 Drug Molecules
Safe and active in lab and animal models
All discovery criteria met
Q. Given about half a million good quality retention times and chemical structures, can we build a model of retention time that would be of use?
Mean Absolute error = 0.23 mini.e. 14 seconds
Chris Luscombe CIX
Initial Filter from a Developability AssayInterpretable rule, filters “bad” compounds, with low false positive rate
in the box are active
Systems for Signal Detection
DEEP Partnership with Lincoln Technologies
This system has now been deployed at FDA, CDC,large Pharma (Pfizer, Lilly, Bayer, BMS, J&J, Roche, AZ)
DEEP (Data Explorationand Evaluation in Pharmacovigilance)
Scientific PublicationsNew strategies to evaluate poly-therapy, drug interactions and demographic “risk factors” for AEs
With post-marketing data, it is difficult to distinguish signals from noise.
Safety Data Mining (SDM)/disproportionality methods identify AEs that are reported with > expected frequency (statistical independence)
Frequency is assessed against the background of all other drugs and events. Results are used for hypothesis generation.
Bayesian methodology to estimate relative reporting rates (risks) of AEs
Enhanced effectiveness of post-marketing pharmacovigilance through rapid, systematic screening of AE databases
Enhanced benefit-risk management
All other Drugs
Event of interest
All other Events
An empirical Bayesian methodology estimates relative reporting rates
Is A>C ??
Wonderex - Rash (16 reports in the database)
0 Drug-Adverse Event Combinations EB05 1 < EB05 2 < EB05 4 < EB05 8 < EB05 <
Had these tools previously been available, critical signalsmight have been identified years before they were recognized with traditional pharmacovigilance. They are now used routinely .
Benefit-risk management-Pharmacovigilance planning Drug-Adverse Event Combinations
Regulatory agency queries
Regulatory submissions for PLEs
Characterizing factors associated with rare serious AEs
Exploring drug interactions and polytherapy in ‘real world use’
Understanding the effects of litigation/publicity on safety signals
Evaluating indication-specific safety profiles in products with multiple indications
Evaluating rare serious events in special populations (i.e., children)
Signal assessment for our co-licensed products
Advisory committee preparationDEEP Provides Information to Reconise Product Performance and Benefit-Risk Ratio:
NSAIDS & COX-2 Inhibitors: Drug-Adverse Event Combinations
AERS to 3Q03(Suspect drugs)
AERS to 3Q03 Drug-Adverse Event Combinations (Suspect drugs)
AERS through 3Q 2003
Chemical Safety: Drug-Adverse Event Combinations
Using human safety data to determine which structural features of drugs contribute to their toxicities
Identify associations between fragments and signals,by calculating diagnostictest statistics.
A positive signal (EB05 5 ) is used as the ”gold standard.” The presenceof a fragment in drug represents a “positive test.”
Identify drug-event pairs with EB055(designate as "signals").
Run datamining algorithm (MGPS).
Create a chemical fragment library for all drug structures in AERS using MoSS to create fragments ranging in size from 4-10 atoms.
Diagnostic test statistics
For a given fragment-event pair:
Odds ratio of 20 means that the odds of having a specific "signal" are 20 times greater if the fragment is present (in the molecule) than if it is not
Positive predictive value of 0.4 means that 40% of drugs containing the fragment will have a “signal” for that adverse event
= nitrogen Drug-Adverse Event Combinations