Quality of Analysis and Selection
"Drug discovery and development involve many iterations of analysis and testing, and analysis means much more than getting statistical correlations," states Alanas Petrauskas, Ph.D., president, Pharma Algorithm (Toronto).
"One has to understand the causal reasons of positive and negative results, suggest viable compound modifications, predict many different ADME-Tox effects for new compounds, extrapolate predictions to physiological levels, identify possible new limiting factors, and select proper experimental assays."
The company's Advanced Algorithm Builder consists of two parts: data analysis tools (algorithm builder) and ADME-Tox predicting tools (ionization, solubility, absorption, oral %F, inhibition, dose dependences, acute and chronic toxicity, mutagenicity, and organ-specific effects, among others).
Analytical tools include automated conversion of experimental data into predictive algorithms. This enables high laboratory automation and allows analyzing experimental data using a knowledge-based approach to understanding the limiting factors that can direct new experiments.
The tools speed up these repetitions by helping "automate" complex decision-making processes. "They differ from traditional informatics tools in that they help to generate new knowledge rather than plain statistics," says Dr. Petrauskas.
"The problem of conventional drug design is that automation compromises quality of analysis and compound selection. Discovery driven by plain statistics is really driven by chance. Without good direction of how to interpret new experimental results, you cannot make good drugs. Virtual screening will become a lot like cherry-picking,' based on the ability to predict most of ADME-Tox effects in silico."
Cyprotex' (Manchester, U.K.) Cyprotex Lead Optimization Engine (Cloe) Screen is an ADME and physicochemical property in vitro screening facility that delivers detailed information on individual compound properties via high throughput robotics and information technology.
Cloe PK prediction software integrates in vitro ADME and physicochemical data to deliver plasma and tissue concentration/ time profiles and PK parameter summary statistics. It enables ranking of compounds based on a compound's likely pharmacokinetics in humans or rats, and provides guidance for scientists to improve pharmacokinetics of individual compounds.
Cloe PK and Screen technologies are integrated with Cyprotex' in-house predictive ADME capability to develop QSAR models from relevant in vitro data within hours of generating that data. These technologies allow users to understand the level and duration of compounds in the body following a particular dose to provide an important basis for interpreting other toxicity and pharmacology data.
Combining Cloe PK results with potency data (such as an IC50 inhibition value), allows determination of the potential efficacy of a compound from a particular dose. Or, if the concentration of a compound that delivers a toxic effect is known, one can see whether or not this level from a particular dose will ever be reached in vivo.
"A key challenge is interpreting in vitro data and extracting the greatest value from it, states Karen Jones, Ph.D., product marketing manager at Cyprotex. "If you have lipophilicity, permeability, metabolism, and solubility data in front of you, which one do you choose to work on first? You need to understand how these properties interplay and consider pharmacokinetics as a whole.
"As in silico technologies become more accepted and better integrated, they will provide a way to consider ADME/PK in drug design stages, so compounds that are synthesized have greater potential for success because they already have good PK properties. This should decrease the need to synthesize vast libraries when this capability is combined with design programs that consider biological properties."