IDBS and Medical Research Council Technology collaboration validates efficacy of PredictionBase, heralding new era of model-based drug discovery
IDBS, provider of drug discovery software, and MRC Technology (MRCT), the technology transfer company associated with the UK's Medical Research Council, today announced that good progress has been made in their malaria research collaboration as a result of adopting model-based drug discovery.
This new approach to research has enabled extremely efficient use of a limited budget.
Using PredictionBase, a new suite of software tools from IDBS for modelling the suitability of compounds as drugs, MRCT researchers were able to predict with 90% accuracy both the active and inactive compounds against a new malarial target.
Having proved the effectiveness of advanced in silico algorithms for the PfSUB-1 assay, which measures inhibition of a protease important in the blood stage of the malarial parasite, MRCT and IDBS will extend the collaboration.
The in silico model generated by PredictionBase will be further refined, to deliver more compounds exhibiting the ADME/tox, efficacy and safety profiles of potential malarial drugs - without the traditional time and expense of large-scale diversity screening.
This breakthrough comes at a time when the pharmaceutical industry is searching for ways to reverse the trend of recent years, which has seen the numbers of new drugs plummet, while research costs have continued to rise.
These results from IDBS and MRCT point to a maturing of predictive technology for drug discovery - proof that such software can complement scientists' expertise to improve predictability and efficiency along the critical path in drug discovery.
PredictionBase from IDBS is a suite of software that brings predictive science to the desktop of every drug discovery researcher.
It encompasses modules for model-building, prediction and library filtering.
Using PredictionBase, scientists capitalise on existing data by creating multi-parameter models that select compounds from virtual libraries most likely to be effective drugs.
As a result, the most promising compounds are given priority for screening and ineffective and unsafe compounds are eliminated sooner.
Early alerts to ADME properties of compounds enable researchers to assess the risk of failure downstream.
PredictionBase's built-in medicinal chemistry expertise uses fragment analysis to suggest strategies for lead optimisation and the creation of new lead series.
"It is estimated that there are 300-500 million cases of malaria annually, leading to between one and two million deaths a year.
"It is a devastating disease.
"The imperative for efficiency and effectiveness in academic malarial drug research is clear, and represents a genuine test of our novel approach to prediction in drug discovery," commented Neil Kipling, chairman and CEO of IDBS.
He continued: "IDBS's vision of model-based drug discovery is to enable organisations to work with the best information at every stage of the drug discovery process.
"Through a framework of consistent data capture, integrated discovery processes and accurate correlated predictions, IDBS provides both the environment and solutions required to shorten the time to market for an increased number of drugs".
In the collaboration between IDBS and MRCT, 10,000 diverse compounds were screened against PfSUB-1, a serine protease malaria target.
The results were used in PredictionBase to develop an in silico model of the assay.
Based on the hits from the primary screen, a follow-up set of compounds was purchased.
The model generated by the software predicted with 90% accuracy the outcome of the blind screening campaign conducted on the follow-up compounds.
"IDBS's PredictionBase provides a logical, rational approach to finding hits and recommending courses of action to improve potency," commented Katy Kettleborough, deputy director of applied research at MRCT.
"Building on the hits we had partially characterised, IDBS's technology and medicinal chemistry expertise allowed us to take a more targeted and intelligent approach to finding more potent molecules rather than simply doing more diversity screening".
Debra Taylor, operations manager assay development group at MRCT, added: "As a result of this collaboration we have been able to progress our malaria programme further than we would otherwise have been in a position to do with our current level of funding.
"The fragments identified by IDBS's new Advanced Logico-Combinatorial Algorithm will give a head-start to any medicinal chemistry approach".
IDBS and MRCT continue to advance the collaboration.
Neil Kipling added, "IDBS is committed to enabling the promising work of MRCT in malaria drug discovery to continue.
"We look forward to working together to generating new compounds with the potential to help overcome this highly destructive disease."
