Hydrolases, Phosphoric Diester

An overview of PGI Analytical Systems, a rapid, computer vision-enabled murine screening system for neuropharmacological activity, is shown in Figure 1. The PGI Analytical Systems training set consisted of hundreds of doses of clinically approved reference drugs, grouped per indication (e.g., anxiolytics, antidepressants, etc.). Drugs were injected 15 min before the test, and multiple challenges were presented over the course of the test session. At least 12 mice were used in each treatment group. Digital videos of the subjects were processed with computer vision algorithms to extract over 2,000 dependent measures including frequency and duration of behavioral states such as grooming, rearing, etc., and many other features obtained during the test session.
A proprietary machine learning algorithm was developed to train a probabilistic classifier that mapped the extracted computer vision feature values from the training set to their corresponding CNS indications. This tool was used to establish a reference database of therapeutic class signatures and provided a mechanism to determine the CNS probabilistic profile of an arbitrary test sample.
Our reference database comprises 14 classes of drugs with some of the major classes, such as the antidepressant class, comprising several subclasses with representatives of most of the drugs in the market. The best performing classifiers during “test set” assessment were chosen from our evaluation tests and two separate types of classifiers were built that make independent predictions: one at the therapeutic class level and one at the level of highly performing subclasses. The behavioral signatures of the test drugs were scored by these classifiers to predict potential therapeutic utility.
To evaluate the ability of the PGI Analytical System to detect relevant behavioral responses to novel compounds, we tested two compounds that represent mechanisms not yet used clinically to treat psychiatric disorders but that impact relevant behavioral endpoints in rodents. The two test compounds, TP-10 and PF-670462, had not been included in the computer algorithm training set. TP-10 is a sub-nanomolar inhibitor of PDE10A, a dual-substrate phosphodiesterase expressed in medium spiny neurons of the striatum that regulates striatal output by regulating both cAMP and cGMP hydrolysis (Strick et al., 2007 ). TP-10 demonstrates multiple behavioral effects in rodents that are consistent with clinically effective antipsychotics, including decreased locomotor activity, inhibition of conditioned avoidance response, and improvement of amphetamine-induced deficits in auditory gating (Schmidt et al., 2008 (link)). PF-670462 is a casein kinase Iε (CK1ε) inhibitor (Badura et al., 2007 (link)).
All compounds were dissolved in a pharmasolve, PEG, PG mixture, and were injected i.p. 15 min before the behavioral test. In a follow-up experiment PF-670462 was administered s.c. 13 h before the behavioral test because of its known effects on circadian rhythm at 50 mg/kg s.c. (Badura et al., 2007 (link)); this procedure was done both in the morning and evening.
As a follow-up test to confirm the anxiolytic signature of PF-670462 we use the marble burying test. PF-670462 was dissolved in 40% cyclodextrin and injected at 10 and 30 mg/kg, s.c. 15 min before the 30-min test. We measured number of marbles buried and distance traveled.
Experimenters were blind to the mechanisms of action of both compounds and to the dose being used. The Institutional Animal Care and Use Committee of PsychoGenics reviewed and approved the animal use in these studies. The animal care and use program is fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care, International.