As the pharmaceutical industry looks for ways to reduce costly failures during clinical phases of development, it is increasingly recognised that leveraging late stage and preclinical research data effectively is crucial for future market competitiveness.
However, whilst many organisations have invested considerable resources to secure data from their early stage screening programs (HTS), emphasis has not been routinely applied to capturing, managing and consolidating data from late stage discovery and preclinical research.
At present there are very few data management solutions that can effectively manage all the data associated with late stage discovery and preclinical research, and this very expensive and valuable data and knowledge is “locked away” in spreadsheet files and documents.
The lack of a cohesive data management solution for this area is unexpected when one considers that this knowledge can represent a research programme’s most valuable assets: the data and knowledge generated from optimised lead candidates that have been selected or rejected for clinical development. Conversely, taking into account the huge diversity of scientific disciplines and the complex undefined nature of the experiments and studies conducted, it is possible to see why this problem has taken so long to solve.
There are a number of well-established scientific disciplines in the preclinical area, each with different workflows and processes.
Mostly scientists involved in pharmacology are interested in the effects of compounds on specific receptor target (micro) response (IC50, EC50, etc) and the associated physiological (macro) response (e.g. a subject scratches more, does not sleep, etc). This area can span both in vitro (plate-based) and in vivo areas of research. At the very high level, researchers look at the macro effects of compounds on behaviour but also investigate the detailed level of the effects of compounds on very precise areas, such as muscle contraction and release of other chemicals.
DMPK (Drug Metabolism and Pharmacokinetics) scientists employ a mixture of in vitro and in vivo methods. Recent technology advances have introduced medium to high throughput plate-based assays using tissue extracts that can be used during the screening and drug optimisation phases of research to predict some PK parameters. However, at some point, the drug must be given to whole animals. These mainstay techniques involve dosing rodents or large mammals, taking blood and other tissue samples at multiple time points and then determining drug concentrations in these samples using mass spectroscopy (LC-MS-MS). Mass spectroscopy data is then analysed using specialist software to calculate parameters such as half-life (T1/2) and Area Under the Curve (AUC) to describe the fate of the drug over time.
Safety pharmacology, sometimes referred to as safety sciences, applies pharmacology techniques to the examination of toxicological endpoints to identify potential undesirable pharmacodynamic effects of substances on physiological function. Safety studies are routinely used both as a screening tool for early drug candidate selection and as a means for predicting issues facing late stage candidates prior to being administered in a clinical setting.
The importance of this rapidly developing field has recently been recognised in newly adopted International Conference on Harmonisation ICH S7A and ICH S7B guidelines, which highlight (S7A) central nervous system, cardiovascular and respiratory system effects as well as (S7B) delayed ventricular depolarisation liability (QTc prolongation). Given the recent interest in cardiovascular issues, and particularly the role of QTc prolongation in predicting cardiac arrhythmias in humans, there has been considerable expansion in the application of both in vitro methodologies (e.g. hERG) as well as ECG monitoring (e.g. radio telemetry) in whole animals. Managing and effectively leveraging the large datasets generated in these growth areas is becoming an emerging challenge.
Scientists in late stage discovery and preclinical research face the following issues:
A data and knowledge management solution for late stage discovery and preclinical research should deliver:
Offering flexible experimental design, direct instrument data capture, native statistics and curve fitting and easy report creation, BioBook delivers a comprehensive, compliant and extensible data management in a single environment. Managing the entire lifecycle of an experiment, BioBook can efficiently and effectively handle all the aspects of in vivo and low throughput in vitro studies in DMPK, pharmacology and safety.