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Numerous investigations have linked mitochondrial dysfunction to adverse health outcomes and drug-induced toxicity. The pharmaceutical industry is challenged with identifying mitochondrial liabilities earlier in drug development and thereby reducing late-stage attrition. Consequently, there is a demand for reliable, higher-throughput screening methods for assessing the impact of drug candidates on mitochondrial function. The extracellular flux (XF) assay described here is a plate-based method in which galactose-conditioned HepG2 cells were acutely exposed to test compounds, then real-time changes in the oxygen consumption rate and extracellular acidification rate were simultaneously measured using a Seahorse Bioscience XF-96 analyzer. The acute XF assay was validated using marketed drugs known to modulate mitochondrial function, and data analysis was automated using a spline curve fitting model developed at GlaxoSmithKline. We demonstrate that the acute XF assay is a robust, sensitive screening platform for evaluating drug-induced effects on mitochondrial activity in whole cells.

Many modern compound-screening technologies are highly miniaturized, resulting in longer-lasting solution stocks in compound management laboratories. As the ages of some stocks stretch into years, it becomes increasingly important to ensure that the DMSO solutions remain of high quality. It can be a burden to check the quality of a large library of compound solutions continuously, and so a study was devised to link the effects of initial compound purity and physicochemical properties of the compounds with the current purity of DMSO solutions. Approximately 5000 compounds with initial purity of at least 80% were examined. Storage conditions were held or observed to be relatively constant and so were eliminated as potential predictors. This allowed the evaluation of the effects of other factors on the stability of solutions, such as initial purity, number of freeze-thaw cycles, age of the solution, and multiple calculated physicochemical parameters. Of all the factors investigated, initial purity was the only one that had a clear effect on stability. None of the other parameters investigated (physicochemical properties, number of freeze-thaw cycles, age of solutions) had a statistically significant effect on stability.

Drug-induced prolongation of the QT interval via block of the hERG potassium channel is a major cause of attrition in drug development. The advent of automated electrophysiology systems has enabled the detection of hERG block earlier in drug discovery. In this study, we have evaluated the suitability of a second generation automated patch clamp instrument, the IonWorks Barracuda, for the characterization of hERG biophysics and pharmacology.All experiments were conducted with cells stably expressing hERG. Recordings were made in perforated patch mode either on a conventional patch clamp setup or on the IonWorks Barracuda. On the latter, all recordings were population recordings in 384-well patch plates.HERG channels activated with a V(1/2)=-3.2±1.6mV (n=178) on the IonWorks Barracuda versus -11.2±6.1mV (n=9) by manual patch clamp. On the IonWorks Barracuda, seal resistances and currents were stable (30% change) with up to six cumulative drug additions and 1-min incubations per addition. Over 27 experiments, an average of 338 concentration-response curves were obtained per experiment (96% of the 352 test wells on each plate). HERG pharmacology was examined with a set of 353 compounds that included well-characterized hERG blockers. Astemizole, terfenadine and quinidine inhibited hERG currents with IC(50) values of 159nM, 224nM and 2μM, respectively (n=51, 10 and 18). This set of compounds was also tested on the PatchXpress automated electrophysiology system. We determined through statistical methods that the two automated systems provided equivalent results.Evaluating drug effects on hERG channels is best performed by electrophysiological methods. HERG activation and pharmacology on the IonWorks Barracuda automated electrophysiology platform were in good agreement with published electrophysiology results. Therefore, the IonWorks Barracuda provides an efficient way to study hERG biophysics and pharmacology.

Human diseases may involve cellular signaling networks that contain redundant pathways, so that blocking a single pathway in the system cannot achieve the desired effect. As such, the use of drugs in combination are particularly effective interventions in networked systems. However, common synergy measures are often inadequate to quantify the effect of two different drugs in complex cellular systems. This article proposes a general approach to quantifying the synergy of two drugs in combination. This approach is called strong nonlinear blending. Drugs with different relative potencies, different effect maxima, or situations of potentiation or coalism pose no problem for strong nonlinear blending as a way to assess the increased response benefit to be gained by combining two drugs. This is important as testing drug combinations in complex biological systems are likely to produce a wide variety of possible response surfaces. It is also shown that for monotone increasing (or decreasing) dose response surfaces that strong nonlinear blending is equivalent to improved potency along a ray of constant dose ratio. This is important because fixed dose ratios form the basis for many preclinical and clinical combination drug experiments. Two examples are given involving HIV and cancer chemotherapy combination drug experiments.

A series of N-hydroxyformamide tumor necrosis factor-alpha converting enzyme (TACE)/matrix metalloprotease (MMP) inhibitors were evaluated for their potential to induce human cytochrome P450 3A (CYP3A). Two in vitro assays were used: 1) a cell-based reporter gene assay for activation of the pregnane X receptor (PXR), and 2) a primary "sandwich" culture of human hepatocytes. Approximately 50 TACE/MMP inhibitors were evaluated in the human PXR assay. A range of PXR activation was observed, 0 to 150% of the activation of the known human CYP3A inducer rifampicin. Three TACE/MMP inhibitors were evaluated in rat and human hepatocytes. Significantly higher PXR activation/CYP3A induction was observed in PXR/hepatocyte models, respectively, for (2R,3S) 3-(formyl-hydroxyamino)-2-(2-methyl-1-propyl)-4-methylpentanoic acid [(1S,2S)-2-methyl-1-(2-pyridylcarbamoyl)-1-butyl]amide (GW3333) compared with (2R,3S)-6,6,6-trifluoro-3-[formyl(hydroxy)amino]-2-isobutyl-N-[(1S,2R)-2-methoxy-1-[(1,3-thiazol-2-ylamino)carbonyl]propyl]hexanamide (GW6495) and (2R)-N-[(1S)-2,2-dimethyl-1-[(methylamino)carbonyl]-propyl]-2-[(1S)-1-[formyl(hydroxy)amino]ethyl]-5-phenylpentanamide (GI4023). The CYP3A induction level achieved with GW3333 at a concentration of approximately 10 microM in human hepatocytes was comparable to that achieved with rifampicin at a concentration of 10 microM. The extent of rodent CYP3A induction caused by GW3333 was confirmed in vivo after daily oral administration for 14 days to rats. In conclusion, GW3333 is a potential inducer of CYP3A expression in vivo in humans, but other N-hydroxyformamides are less likely to induce CYP3A.

Under the Loewe additivity, constant relative potency between two drugs is a sufficient condition for the two drugs to be additive. Implicit in this condition is that one drug acts like a dilution of the other. Geometrically, it means that the dose-response curve of one drug is a copy of another that is shifted horizontally by a constant over the log-dose axis. Such phenomenon is often referred to as parallelism. Thus, testing drug additivity is equivalent to the demonstration of parallelism between two dose-response curves. Current methods used for testing parallelism are usually based on significance tests for differences between parameters in the dose-response curves of the monotherapies. A p-value of less than 0.05 is indicative of non-parallelism. The p-value-based methods, however, may be fundamentally flawed because an increase in either sample size or precision of the assay used to measure drug effect may result in more frequent rejection of parallel lines for a trivial difference. Moreover, similarity (difference) between model parameters does not necessarily translate into the similarity (difference) between the two response curves. As a result, a test may conclude that the model parameters are similar (different), yet there is little assurance on the similarity between the two dose-response curves. In this paper, we introduce a Bayesian approach to directly test the hypothesis that the two drugs have a constant relative potency. An important utility of our proposed method is in aiding go/no-go decisions concerning two drug combination studies. It is illustrated with both a simulated example and a real-life example.

A method for detecting deviations from the Loewe additive drug combination reference model for in vitro drug combination experimentation is described. It is often difficult to fit a response surface model to drug combination data, especially in situations where the experimental design contains a sparse set of combinations. The literature does contain good response surface modeling approaches, but they tend to be complex and can be difficult to execute. It is especially difficult to check model quality when fitting to more than two combined agents. A simple method based on sound statistical principles is proposed that examines the mean response deviation of each combination from the predicted response under Loewe additivity. The method can readily handle any number of combined agents, does not require sophisticated modeling, and can even be programmed into Microsoft Excel without the use of macros. Several potential extensions to the method are discussed in detail. Computer-generated simulations demonstrate the statistical capabilities of the approach, and a real-data example is given to illustrate the method.

Clinical trials of the first approved integrase inhibitor (INI), raltegravir, have demonstrated a drop in the human immunodeficiency virus type 1 (HIV-1) RNA loads of infected patients that was unexpectedly more rapid than that with a potent reverse transcriptase inhibitor, and apparently dose independent. These clinical outcomes are not understood. In tissue culture, although their inhibition of integration is well documented, the effects of INIs on levels of unintegrated HIV-1 cDNAs have been variable. Furthermore, there has been no report to date on an INI's effect on these episomal species in vivo. Here, we show that prophylactic treatment of transgenic rats with the strand transfer INI GSK501015 reduced levels of viral integrants in the spleen by up to 99.7%. Episomal two-long-terminal-repeat (LTR) circles accumulated up to sevenfold in this secondary lymphoid organ, and this inversely correlated with the impact on the proviral burden. Contrasting raltegravir's dose-ranging study with HIV patients, titration of GSK501015 in HIV-infected animals demonstrated dependence of the INI's antiviral effect on its serum concentration. Furthermore, the in vivo 50% effective concentration calculated from these data best matched GSK501015's in vitro potency when serum protein binding was accounted for. Collectively, this study demonstrates a titratable, antipodal impact of an INI on integrated and episomal HIV-1 cDNAs in vivo. Based on these findings and known biological characteristics of viral episomes, we discuss how integrase inhibition may result in additional indirect antiviral effects that contribute to more rapid HIV-1 decay in HIV/AIDS patients.