DATA ANALYSIS IN PHARMACOLOGY STRAIGHT DOWN THE LIM
Trish Meek, director of Product Strategy, Life Sciences, at Thermo Fisher Scientific, comments: ‘Understanding how the body metabolises drugs and ensuring the safety and efficacy of not only the initial drug substance, but also all of its metabolites is a critical step in the drug development process. The key is elimination of poor candidates as early as possible in the process, ensuring that only the strongest candidates reach clinical trials. ‘Today, this work often begins
with in silico testing. Once the computer models identify a strong
candidate, in vitro work can begin. ADME/Tox (Absorption, Distribution, Metabolism, Excretion and Toxicology) has permitted researchers to eliminate poor candidates earlier in the development process. The trade-off is that in vitro testing has created a deluge of data and required pharmaceutical companies to look at how they handle throughput, storage and analysis. An informatics solution, like a LIMS, is critical to the success of these laboratories as they enable companies to increase their throughput and decrease
products leave the user to understand that their specifics are simply the application of general statistical principles. Te manual for Unistat, a general statistics package popular with life science researchers, adopts the halfway-house approach of providing discipline contextualised examples, such as using multiple dose response curves to demonstrate nonlinear logistic regression. SPSS, with its heritage firmly fixed in
the sciences, is a popular choice that crops up in a wide spread of contexts. Soſtware with an emphasis on plotting or other visualisation approaches is widely used. GraphPad’s Prism, for instance, recurs in several studies, such as an investigation[3]
Compound view of dose response curve generation in Unistat 6.0
of
pharmacological calcium channel blocking to reduce chronic pain in sufferers irritable bowel syndrome. Te objective here, in a set of experiments using rodents, was to compare ionic conductance contributing to neuronal firing to identify most likely analgesic approaches; difference analyses were therefore central.
TIME AND TIDE
Physiological changes accompanying the aging process can alter pharmacological response. Using Statistica, a collaborative academic, medical and pharmaceutical industry team led by Catherine Goh investigated the ways in which pharmacological properties of cholinesterase inhibitors (used in the treatment of Alzheimer’s disease) differ in this respect. Some agents were shown to remain close to constant in bioavailability and effect, while pharmacodynamic sensitivity to others increased with age as did certain pharmacologically mediated collateral effects. Decrease in a specific receptor expression as organisms age was suggested as possibly being part of the explanation.[9]
20 BEYOND THE NUMBERS A STATISTICS SPECIAL Packages with a life science background
to their evolution are obviously going to be popular in this area, an assumption borne out by plaudits for VSNi’s GenStat (see box: What’s a mother to do? For example). Given the immense volumes of data generated by some pharmacological studies, they are an obvious candidate for data mining. Statsoſt’s Statistica is well represented in its own right (as in the Time and tide box), but its Data Miner module is also found in several programmes which seek to reuse research by harvesting existing and ever-growing databases of past results. As Termo Fisher’s Trish Meek sketches
out (see box: Straight down the LIM), the blizzard of data which arises from the successive phases of pharmacological investigations needs to be contained and managed. ELN (Electronic Laboratory Notebook) and LIMS (Laboratory Information Management System) soſtware are these days essential to data analysis in many areas of science – a trend of which pharmacology is a prime example. Such
overall costs by automating the ADME process from initial data acquisition through analysis and review to the ultimate acceptance of the data. By implementing a data management system, one of our global pharmaceutical LIMS customers was able to increase their Tier 1 ADME compounds screening rate to more than 2,000 compounds a week. ‘Following in vitro testing, in vivo animal studies are conducted to determine which candidates should proceed to clinical trial. Bioanalytical labs run studies, performing drug metabolism
(DM) and Pharmacokinetics/ Pharmacodynamics (PK/PD) analysis on the samples to determine their profile in the human body and ensure good drug clearance, safety, and efficacy in the test animals. ‘Again, data management is critical for managing the study design and execution to ensure that runs are performed correctly, and to determine the final results to submit to the FDA in the new drug application. A good LIMS system, like our Watson, promotes good practice and effective study management.’
systems are as much of a specialism as pharmacology itself and the expertise which their suppliers amass is similarly so. Tough LIMS are sold by numerous
suppliers at various scales and there is at least one inventorying example – Quartzy, run on a free to use bottom up basis – those which can cope with the pharmacological volume of major investment programmes’ expertise come from a few suppliers. Te Watson LIMS mentioned by Meek, for instance, has been adopted by a substantial majority of the world’s largest pharmaceutical laboratories. In common with most areas of data
management, there is currently a move towards distributed cloud approaches although, given the investment levels oſten involved, security remains an issue. Provider Core LIMS makes a point of emphasising that its modular solutions are entirely web-based, accessible from wherever the client has authorised users, but can either be installed on a client’s in-situ local servers or remotely cloud hosted.
References and Sources
For a full list of references and sources cited in this article, visit
www.scientific-computing.com/features/referencesapr12.php
FURTHER INFORMATION CoreLIMS
www.corelims.com/pharmaceuticallims.htm GraphPad
www.graphpad.com/prism/Prism.htm IBM
www-01.ibm.com/software/analytics/spss/products/statistics InVivoStat
invivostat.co.uk Quartzy
www.quartzy.com Statsoft
www.statsoft.co.uk/main.php?t=i&p=products Thermo Fisher Scientific
www.thermofisher.com Unistat
www.unistat.com VSN International
www.vsni.co.uk/software/genstat
SCIENTIFIC COMPUTING WORLD
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