A Symbolic Regression Model for the Prediction of Drug Binding to Human Liver Microsomes.

It is common practice in the early drug discovery process to conduct in vitro screening experiments using liver microsomes in order to obtain an initial assessment of test compound metabolic stability. Compounds which bind to liver microsomes are unavailable for interaction with the drug metabolizing enzymes. As such, assessment of the unbound fraction of compound available for biotransformation is an important factor for interpretation of in vitro experimental results and to improve prediction of the in vivo metabolic clearance. Various in silico methods have been proposed for the prediction of test compound binding to microsomes, from various simple lipophilicity-based models with moderate performance to sophisticated machine learning models which demonstrate superior performance at the cost of increased complexity and higher data requirements. In this work, we attempt to strike a middle ground by developing easily implementable equations with improved predictive performance. We employ a symbolic regression approach based on a medium-size in-house data set of fraction unbound in human liver microsomes measurements allowing the identification of novel equations with improved performance. We validate the model performance on an in-house held-out test set and an external validation set.

Unbound Brain-to-Plasma Partition Coefficient, Kp,uu,brain-a Game Changing Parameter for CNS Drug Discovery and Development.

PURPOSE: More than 15 years have passed since the first description of the unbound brain-to-plasma partition coefficient (Kp,uu,brain) by Prof. Margareta Hammarlund-Udenaes, which was enabled by advancements in experimental methodologies including cerebral microdialysis. Since then, growing knowledge and data continue to support the notion that the unbound (free) concentration of a drug at the site of action, such as the brain, is the driving force for pharmacological responses. Towards this end, Kp,uu,brain is the key parameter to obtain unbound brain concentrations from unbound plasma concentrations. METHODS: To understand the importance and impact of the Kp,uu,brain concept in contemporary drug discovery and development, a survey has been conducted amongst major pharmaceutical companies based in Europe and the USA. Here, we present the results from this survey which consisted of 47 questions addressing: 1) Background information of the companies, 2) Implementation, 3) Application areas, 4) Methodology, 5) Impact and 6) Future perspectives. RESULTS AND CONCLUSIONS: From the responses, it is clear that the majority of the companies (93%) has established a common understanding across disciplines of the concept and utility of Kp,uu,brain as compared to other parameters related to brain exposure. Adoption of the Kp,uu,brain concept has been mainly driven by individual scientists advocating its application in the various companies rather than by a top-down approach. Remarkably, 79% of all responders describe the portfolio impact of Kp,uu,brain implementation in their companies as 'game-changing'. Although most companies (74%) consider the current toolbox for Kp,uu,brain assessment and its validation satisfactory for drug discovery and early development, areas of improvement and future research to better understand human brain pharmacokinetics/pharmacodynamics translation have been identified.

Mechanistic understanding of brain drug disposition to optimize the selection of potential neurotherapeutics in drug discovery.

PURPOSE: The current project was undertaken with the aim to propose and test an in-depth integrative analysis of neuropharmacokinetic (neuroPK) properties of new chemical entities (NCEs), thereby optimizing the routine of evaluation and selection of novel neurotherapeutics. METHODS: Forty compounds covering a wide range of physicochemical properties and various CNS targets were investigated. The combinatory mapping approach was used for the assessment of the extent of blood-brain and cellular barriers transport via estimation of unbound-compound brain (Kp,uu,brain) and cell (Kp,uu,cell) partitioning coefficients. Intra-brain distribution was evaluated using the brain slice method. Intra- and sub-cellular distribution was estimated via calculation of unbound-drug cytosolic and lysosomal partitioning coefficients. RESULTS: Assessment of Kp,uu,brain revealed extensive variability in the brain penetration properties across compounds, with a prevalence of compounds actively effluxed at the blood-brain barrier. Kp,uu,cell was valuable for identification of compounds with a tendency to accumulate intracellularly. Prediction of cytosolic and lysosomal partitioning provided insight into the subcellular accumulation. Integration of the neuroPK parameters with pharmacodynamic readouts demonstrated the value of the proposed approach in the evaluation of target engagement and NCE selection. CONCLUSIONS: With the rather easily-performed combinatory mapping approach, it was possible to provide quantitative information supporting the decision making in the drug discovery setting.

Optimising wound care in a child with an infected gastrostomy exit site.

The percutaneous endoscopic gastrostomy (PEG) tube has become a widely used feeding tube for long-term delivery of fluids, liquid feed and medicines. PEG tube insertion can be considered a minimally invasive technique, associated with rapid recovery and early discharge from hospital but is not without risk (Vervloessem et al 2009; Naiditch et al 2010). A lack of nationally agreed, evidence-based clinical practice guidelines makes PEG exit site care a matter of local clinical practice and clinical judgement. In paediatric practice, children experience care shared across several healthcare settings, meeting clinical teams with varying levels of knowledge and experience of PEG care. This can lead to conflicting advice, which can have a negative effect on patient safety and experience. The case history in this article demonstrates how PEG tube insertion is never a minor procedure for a child and family (Vervloessem et al 2009; Khattak et al 1998). It highlights areas of potential conflict in clinical management of PEG exit sites, and it shows how application of wound care principles, along with a range of modern products can have a positive outcome.

Development and implementation of an enterprise-wide predictive model for early absorption, distribution, metabolism and excretion properties.

Background: Accurate prediction of absorption, distribution, metabolism and excretion (ADME) properties can facilitate the identification of promising drug candidates. Methodology & Results: The authors present the Janssen generic Target Product Profile (gTPP) model, which predicts 18 early ADME properties, employs a graph convolutional neural network algorithm and was trained on between 1000-10,000 internal data points per predicted parameter. gTPP demonstrated stronger predictive power than pretrained commercial ADME models and automatic model builders. Through a novel logging method, the authors report gTPP usage for more than 200 Janssen drug discovery scientists. Conclusion: The investigators successfully enabled the rapid and systematic implementation of predictive ML tools across a drug discovery pipeline in all therapeutic areas. This experience provides useful guidance for other large-scale AI/ML deployment efforts.

The fluorescent two-hybrid assay to screen for protein-protein interaction inhibitors in live cells: targeting the interaction of p53 with Mdm2 and Mdm4.

Protein-protein interactions (PPIs) are attractive but challenging targets for drug discovery. To overcome numerous limitations of the currently available cell-based PPI assays, we have recently established a fully reversible microscopy-assisted fluorescent two-hybrid (F2H) assay. The F2H assay offers a fast and straightforward readout: an interaction-dependent co-localization of two distinguishable fluorescent signals at a defined spot in the nucleus of mammalian cells. We developed two reversible F2H assays for the interactions between the tumor suppressor p53 and its negative regulators, Mdm2 and Mdm4. We then performed a pilot F2H screen with a subset of compounds, including small molecules (such as Nutlin-3) and stapled peptides. We identified five cell-penetrating compounds as potent p53-Mdm2 inhibitors. However, none exhibited intracellular activity on p53-Mdm4. Live cell data generated by the F2H assays enable the characterization of stapled peptides based on their ability to penetrate cells and disrupt p53-Mdm2 interaction as well as p53-Mdm4 interaction. Here, we show that the F2H assays enable side-by-side analysis of substances' dual Mdm2-Mdm4 activity. In addition, they are suitable for testing various types of compounds (e.g., small molecules and peptidic inhibitors) and concurrently provide initial data on cellular toxicity. Furthermore, F2H assays readily allow real-time visualization of PPI dynamics in living cells.

Development and validation of a higher-throughput equilibrium dialysis assay for plasma protein binding.

We describe the practical aspects of developing a semiautomated, higher-throughput plasma protein binding (PPB) assay. The assay has a capacity of 32 PPB measurements per screen using triplicate incubations per measurement, and it is flexible with respect to the number of compounds and the number of plasma types used. The described method is based on the 48-well format rapid equilibrium dialysis (RED) device in combination with a robotic liquid handling platform and quantitative bioanalysis. The RED device method was optimized with respect to equilibration time. Method validation was performed by comparison of results from the semiautomated RED PPB assay with both of those obtained using an alternative, manual equilibrium dialysis method and with literature values. Propranolol and warfarin were used as control compounds. We have modeled the effect of dialysis membrane leakage on the measured unbound fraction and implemented a test for measuring protein content in the buffer compartment to confirm the integrity of each insert of the RED device. With the described method, it is possible to screen a relatively large number of compounds for PPB in a drug discovery environment.

Prediction of human oral plasma concentration-time profiles using preclinical data: comparative evaluation of prediction approaches in early pharmaceutical discovery.

BACKGROUND AND OBJECTIVES: Empirically based methods remain one of our tools in human pharmacokinetic predictions. The Dedrick approach and the steady-state plasma drug concentration (C(ss))-mean residence time (MRT) approach are based on the assumption that concentration-time profiles are similar among species, including man, and that curves derived from a variety of animal species can be superimposed after mathematical transformation. In the Dedrick approach the transformation is based on the slope and intercept of the allometric relationship. The C(ss)-MRT approach is based on the implementation of measured animal and predicted human MRT and dose/volume of distribution at steady state (V(ss)). The aims of the present study were to compare the predictive performance of concentration-time profiles obtained by these approaches, to evaluate the prediction of individual pharmacokinetic parameters by these approaches and to further refine these approaches incorporating the experience from our previous work. METHODS: A retrospective analysis using 35 proprietary compounds developed at Johnson & Johnson Pharmaceutical Research and Development was conducted to compare the accuracies of the Dedrick and C(ss)-MRT approaches for predicting oral concentration-time profiles and pharmacokinetic parameters in man. In the first step, input for the transformation was based on simple allometry. Then we assessed whether both methods could be fine-tuned by systematically incorporating correction factors (maximum life span potential, brain weight and plasma protein binding), depending on the interspecies relationship. In addition, for the C(ss)-MRT approach, we used formulas based on multivariate regression analysis as input for the transformation. RESULTS: Inclusion of correction factors significantly improved the profile predictability for the Dedrick and C(ss)-MRT approaches. This was mainly linked to an improved prediction of terminal elimination half-life (t(½)), MRT and the ratio between the maximum plasma concentration and the concentration at the last observed time point (C(max)/C(last)). No significant differences were observed between the Dedrick approach with correction factors, the C(ss)-MRT approach with correction factors and the C(ss)-MRT approach, based on the regression equations. CONCLUSIONS: Based on the dataset evaluated in this study, we demonstrated that human plasma concentration-time profiles and pharmacokinetic parameters could be predicted with the Dedrick and C(ss)-MRT approaches and that if correction factors were implemented, the predictions improved significantly. With the requirement of only a limited preclinical in vivo pharmacokinetic dataset, these empirical methods could offer potential in the early stages of drug discovery.

Ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry for robust, high-throughput quantitative analysis of an automated metabolic stability assay, with simultaneous determination of metabolic data.

The application of ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) for high-throughput analysis of a 96-well plate based metabolic stability assay has been investigated. Full-scan data were acquired, with run times of 2.5-3.5 min, from which narrow window extracted ion chromatograms were generated, producing quantitative data for the test compound equivalent to that obtained by high-performance liquid chromatography with tandem mass spectrometric detection on a triple quadrupole instrument (HPLC/MS/MS). Sensitivity and mass accuracy were maintained over the analysis of >300 samples. Additionally, the UPLC/TOFMS datasets obtained gave access to metabolic route information, at no cost in terms of sensitivity for the test compound.

The search for novel TRPV1-antagonists: from carboxamides to benzimidazoles and indazolones.

Based on a series of diaryl amides the corresponding inverse amides have been found to be potent TRPV1 receptor antagonists. Benzimidazole and indazolone derivatives prepared retained good potency in vitro and indazolone 4a was identified as a novel TRPV1 receptor antagonist suitable for evaluating orally in animal models of analgesia.

An evaluation of a four-channel multiplexed electrospray tandem mass spectrometry for higher throughput quantitative analysis.

A four-channel multiplexed electrospray inlet system (MUX) coupled to a triple quadrupole mass spectrometer was investigated as a higher throughput approach to quantitative analysis. Four discrete samples may be simultaneously analyzed by virtue of a rotating sampler with a concomitant 4-fold increase in analytical throughput. Although absolute sensitivity was reduced using the MUX interface compared with analysis using traditional single electrospray interface, reproducibility of response was shown to be comparable. Source robustness was established for the analysis of both aqueous drug standards and drugs in biological media, and linearity of response for a test compound, diazepam, was demonstrated over 2 orders of magnitude. Analyte-dependent response differences were exhibited between the four channels of the interface, and this led to the overall conclusion that samples to be compared quantitatively must be analyzed through the same sprayer. In addition, each channel must be independently calibrated to afford true quantification. Should a deuterated internal standard be employed, however, quantitative comparisons can be made across channels. An HPLC pumping system providing individual back-pressure regulation to each channel was shown to provide adequate chromatography even in the event of a channel blockage. Furthermore, following multiple injections of biological samples onto the MUX interface, an eluent flow diversion was integrated into the first part of each analytical run. This served to prevent source fouling, and thus, no detrimental effects to response reproducibility or sensitivity were observed.

Determination of drug concentrations in plasma by a highly automated, generic and flexible protein precipitation and liquid chromatography/tandem mass spectrometry method applicable to the drug discovery environment.

This report presents a highly automated procedure for the determination of drug concentrations in plasma samples. The method is generic, in that it has been applied without adaptation to many different drug candidate molecules, but is also flexible, in that variations in the nature and number of samples to be analyzed can be readily accommodated. The method includes preparation of dilutions of analyte stock solutions, spiking these into control plasma to generate analytical standards, and preparation of samples suitable for analysis by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS) by precipitation of plasma proteins with acetonitrile, centrifugation, and dilution of the supernatants with HPLC buffer. All of these steps, apart from centrifugation, are performed without manual intervention on an automated liquid-handling workstation using 96-well plates. Analysis is by HPLC/MS/MS, using a generic HPLC gradient. Commercially available software was used for optimization of parameters for analysis by HPLC/MS/MS, integration of chromatographic peaks, and quantification of drug concentrations. The use of this methodology in our laboratory has greatly facilitated the analysis of small sample sets for a large number of analytes, a situation regularly encountered in an early drug discovery environment.

Identification of metabolites of a substance P (neurokinin 1 receptor) antagonist in rat hepatocytes and rat plasma.

[3R,5R,6S]-3-(2-cyclopropyloxy-5-trifluoromethoxyphenyl)-6-phenyl-1-oxa-7-azaspiro[4.5]decane is a substance P (Neurokinin 1 receptor) antagonist. Substance P antagonists are proven in concept to have excellent potential for the treatment of major depression, and they allow superior and sustained protection from acute and delayed chemotherapy-induced emesis. The metabolism of this compound was investigated in rat hepatocytes, and circulating rat plasma metabolites were identified following oral and intravenous dosing. The turnover in rat hepatocytes within 4 h was about 30%, and the major metabolites were identified as two nitrones and a lactam associated with the piperidine ring. Although these metabolites were also observed in rat plasma, the major circulating metabolite was a keto acid following oxidative de-amination of the piperidine ring. Liquid chromatography/tandem mass spectrometry and nuclear magnetic resonance were used to confirm the structure of the latter metabolite. A mechanism leading to the formation of the keto acid metabolite has been suggested, and most intermediates were observed in rat plasma.