In Vitro Intrinsic Permeability: A Transporter-Independent Measure of Caco-2 Cell Permeability in Drug Design and Development

A Machine Learning Approach for Predicting Caco-2 Cell Permeability in Natural Products from the Biodiversity in Peru

BACKGROUND

Peru is one of the most biodiverse countries in the world, which is reflected in its wealth of knowledge about medicinal plants. However, there is a lack of information regarding intestinal absorption and the permeability of natural products. The human colon adenocarcinoma cell line (Caco-2) is an in vitro assay used to measure apparent permeability. This study aims to develop a quantitative structure-property relationship (QSPR) model using machine learning algorithms to predict the apparent permeability of the Caco-2 cell in natural products from Peru.

METHODS

A dataset of 1817 compounds, including experimental log Papp values and molecular descriptors, was utilized. Six QSPR models were constructed: a multiple linear regression (MLR) model, a partial least squares regression (PLS) model, a support vector machine regression (SVM) model, a random forest (RF) model, a gradient boosting machine (GBM) model, and an SVM-RF-GBM model.

RESULTS

An evaluation of the testing set revealed that the MLR and PLS models exhibited an RMSE = 0.47 and R2 = 0.63. In contrast, the SVM, RF, and GBM models showcased an RMSE = 0.39-0.40 and R2 = 0.73-0.74. Notably, the SVM-RF-GBM model demonstrated superior performance, with an RMSE = 0.38 and R2 = 0.76. The model predicted log Papp values for 502 natural products falling within the applicability domain, with 68.9% (n = 346) showing high permeability, suggesting the potential for intestinal absorption. Additionally, we categorized the natural products into six metabolic pathways and assessed their drug-likeness.

CONCLUSIONS

Our results provide insights into the potential intestinal absorption of natural products in Peru, thus facilitating drug development and pharmaceutical discovery efforts.

The in vitro intestinal cell model: different co-cultured cells create different applications

As a vitro absorption model, the Caco-2 cells originate from a human colon adenocarcinomas and can differentiate into a cell layer with enterocyte-like features. The Caco-2 cell model is popularly applied to explore drug transport mechanisms, to evaluate the permeability of drug and to predict the absorption of drugs or bioactive substances in the gut. However, there are limitations to the application of Caco-2 cell model due to lack of a mucus layer, the long culture period and the inability to accurately simulate the intestinal environment. The most frequent way to expand the Caco-2 cell model and address its limitations is by co-culturing it with other cells or substances. This article reviews the culture methods and applications of 3D and 2D co-culture cell models established around Caco-2 cells. It also concludes with a summary of model strengths and weaknesses.

Synthesis of salcaprozate sodium and its significance in enhancing pancreatic kininogenase absorption performance

We conducted pharmacokinetic research wherein salcaprozate sodium (SNAC) was utilized as a penetration enhancer by incorporating it into pancreatic kininogenase (PK) to improve the bioavailability of pancreatic kininogenase enteric-coated tablets. We conducted in vitro studies on PK using the Caco-2 cell model and quantified PK levels using the enzyme-linked immunosorbent assay (ELISA) method. We conducted methodological verification by blending SNAC and PK powders into enteric-coated capsules, and studied the pharmacokinetic characteristics. Based on the PK transport assay, the cumulative permeation rates of the test group that employed a SNAC to PK ratio of 32:1, 16:1, 8:1, 4:1, and 2:1 were 13.574%, 7.597%, 10.653%, 3.755%, and 2.523%, respectively. We conducted a uniformity test on the powder that contained a blend of SNAC and PK. The relative standard deviations (RSDs) for both the power containing SNAC and the power not containing SNAC were less than 10%. Based on the methodological verification, in vivo pharmacokinetic study of PK met the experimental requirements. As indicated by the results of in vivo pharmacokinetic research on rats, the test group (This group used SNAC) had a PK AUC0-12 h of 5679.747 ng/L*h and t1/2 of 4.569 h, while the control group (This group did not use SNAC) had a PK AUC0-12 h of 4639.665 ng/L*h and t1/2 of 3.13 h. This study has established a low-cost, environmentally friendly, and safe SNAC synthesis route with high process yield suitable for industrial production. SNAC demonstrates an absorption-enhancing effect on PK, and the optimal ratio of SNAC to PK is determined to be 32:1.

A new workflow for the effective curation of membrane permeability data from open ADME information

Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data. An open database offers extensive measurements of various compounds covering a vast chemical space; however, concerns were reported on the use of data published in open databases without the appropriate accuracy and quality checks. Ensuring the quality of datasets for training in silico models is critical because artificial intelligence (AI, including deep learning) was used to develop models to predict various pharmacokinetic properties, and data quality affects the performance of these models. Hence, careful curation of the collected data is imperative. Herein, we developed a new workflow that supports automatic curation of Papp data measured in the MDCK, LLC-PK1, and RRCK cell lines collected from ChEMBL using KNIME. The workflow consisted of four main phases. Data were extracted from ChEMBL and filtered to identify the target protocols. A total of 1661 high-quality entries were retained after checking 436 articles. The workflow is freely available, can be updated, and has high reusability. Our study provides a novel approach for data quality analysis and accelerates the development of helpful in silico models for effective drug discovery. Scientific Contribution: The cost of building highly accurate predictive models can be significantly reduced by automating the collection of reliable measurement data. Our tool reduces the time and effort required for data collection and will enable researchers to focus on constructing high-performance in silico models for other types of analysis. To the best of our knowledge, no such tool is available in the literature.

Utilizing a Dual Human Transporter MDCKII-MDR1-BCRP Cell Line to Assess Efflux at the Blood Brain Barrier

To facilitate the design of drugs readily able to cross the blood brain barrier (BBB), a Madin-Darby canine kidney (MDCK) cell line was established that over expresses both P-glycoprotein (Pgp) and breast cancer resistance protein (BCRP), the main human efflux transporters of the BBB. Proteomics analyses indicate BCRP is expressed at a higher level than Pgp in this cell line. This cell line shows good activity for both transporters [BCRP substrate dantrolene efflux ratio (ER) 16.3 ± 0.9, Pgp substrate quinidine ER 27.5 ± 1.2], and use of selective transporter inhibitors enables an assessment of the relative contributions to overall ERs. The MDCKII-MDR1-BCRP ER negatively correlates with rat unbound brain/unbound plasma ratio, Kpuu Highly brain penetrant compounds with rat Kpuu ≥ 0.3 show ERs ≤ 2 in the MDCKII-MDR1-BCRP assay while compounds predominantly excluded from the brain, Kpuu ≤ 0.05, demonstrate ERs ≥ 20. A subset of compounds with MDCKII-MDR1-BCRP ER < 2 and rat Kpuu < 0.3 were shown to be substrates of rat Pgp using a rat transfected cell line, MDCKII-rMdr1a. These compounds also showed ERs > 2 in the human National Institutes of Health (NIH) MDCKI-MDR1 (high Pgp expression) cell line, which suggests that they are weak human Pgp substrates. Characterization of 37 drugs targeting the central nervous system in the MDCKII-MDR1-BCRP efflux assay show 36 have ERs < 2. In drug discovery, use of the MDCKII-MDR1-BCRP in parallel with the NIH MDCKI-MDR1 cell line is useful for identification of compounds with high brain penetration. SIGNIFICANCE STATEMENT: A single cell line that includes both the major human efflux transporters of the blood brain barrier (MDCKII-MDR1-BCRP) has been established facilitating the rapid identification of efflux substrates and enabling the design of brain penetrant molecules. Efflux ratios using this cell line demonstrate a clear relationship with brain penetration as defined by rat brain Kpuu.

Experiences and Translatability of In Vitro and In Vivo Models to Evaluate Caprate as a Permeation Enhancer

Transient permeation enhancers (PEs) have been widely used to improve the oral absorption of macromolecules. During pharmaceutical development, the correct selection of the macromolecule, PE, and the combination needs to be made to maximize oral bioavailability and ensure successful clinical development. Various in vitro and in vivo methods have been investigated to optimize this selection. In vitro methods are generally preferred by the pharmaceutical industry to reduce the use of animals according to the "replacement, reduction, and refinement" principle commonly termed "3Rs," and in vitro methods typically have a higher throughput. This paper compares two in vitro methods that are commonly used within the pharmaceutical industry, being Caco-2 and an Ussing chamber, to two in vivo models, being in situ intestinal instillation to rats and in vivo administration via an endoscope to pigs. All studies use solution formulation of sodium caprate, which has been widely used as a PE, and two macromolecules, being FITC-dextran 4000 Da and MEDI7219, a GLP-1 receptor agonist peptide. The paper shares our experiences of using these models and the challenges with the in vitro models in mimicking the processes occurring in vivo. The paper highlights the need to consider these differences when translating data generated using these in vitro models for evaluating macromolecules, PE, and combinations thereof for enabling oral delivery.

Kinetic modelling of the P-glycoprotein mediated efflux with a large-scale matched molecular pair analysis

P-glycoprotein (Pgp) mediated efflux impacts on the drug absorption, distribution, metabolism and excretion, and confers multidrug resistance to cancer cells. Kinetic modelling provides mechanistic insights into the relationship between the substrate-Pgp interactions and efflux, and bridges the gap between the preference of polar compounds as Pgp substrates and the hydrophobic nature of its drug-binding site. Matched molecular pair analysis supports the guidelines of controlling H-bond donors and polar surface area in the efflux mitigation, but also reveals insufficiency of this type of rule-based approach. Contrary to the rule-of-five compliant compounds, proteolysis-targeting chimeras (PROTACs) have shown the opposite preference of physicochemical properties to evade efflux. Our analysis reiterates the critical role of intrinsic passive permeability in the efflux ratio, and indeed, its mitigation is often driven by increased passive permeability. It is thus useful to separate the passive permeability from the structural context-specific substrate-Pgp interactions in the design cycle.

Approaches to Account for Colon Absorption in Physiologically Based Biopharmaceutics Modeling of Extended-Release Drug Products

The rate and extent of colon absorption are important determinants of the in vivo performance of extended-release (ER) drug products. The ability to appropriately predict this at different stages of development using mechanistic physiologically based biopharmaceutic modeling (PBBM) is highly desirable. This investigation aimed to evaluate the prediction performance of three different approaches to account for colon absorption in predictions of the in vivo performance of ER drug product variants with different in vitro release profiles. This was done by mechanistic predictions of the absorption and plasma exposure of the ER drug products using GastroPlus and GI-Sim for five drugs with different degrees of colon absorption limitations in humans. Colon absorption was accounted for in the predictions using three different approaches: (1) by an a priori approach using the default colon models, (2) by fitting the colon absorption scaling factors to the observed plasma concentration-time profiles after direct administration to the colon in humans, or (3) from the ER drug product variant with the slowest in vitro release profile. The prediction performance was evaluated based on the percentage prediction error and the average absolute prediction error (AAPE). Two levels of acceptance criteria corresponding to highly accurate (AAPE ≤ 20%) and accurate (AAPE 20-50%) predictions were defined prior to the evaluation. For the a priori approach, the relative bioavailability (Frel), AUC0-t, and Cmax of the ER drug product variants for the low to medium colon absorption limitation risk drugs was accurately predicted with an AAPE range of 11-53 and 8-59% for GastroPlus and GI-Sim, respectively. However, the prediction performance was poor for the high colon absorption limitation risk drugs. Moreover, accounting for the human regional colon absorption data in the models did not improve the prediction performance. In contrast, using the colon absorption scaling factors derived from the slowest ER variant significantly improved the prediction performance regardless of colon absorption limitation, with a majority of the predictions meeting the high accuracy criteria. For the slowest ER approach, the AAPE ranges were 5-24 and 5-32% for GastroPlus and GI-Sim, respectively, excluding the low permeability drug. In conclusion, the a priori PBBM can be used during candidate selection and early product design to predict the in vivo performance of ER drug products for low to medium colon absorption limitation risk drugs with sufficient accuracy. The results also indicate a limited value in performing human regional absorption studies in which the drug is administered to the colon as a bolus to support PBBM development for ER drug products. Instead, by performing an early streamlined relative bioavailability study with the slowest relevant ER in vitro release profile, a highly accurate PBBM suitable for ER predictions for commercial and regulatory applications can be developed, except for permeability-limited drugs.

Challenges in Permeability Assessment for Oral Drug Product Development

Drug permeation across the intestinal epithelium is a prerequisite for successful oral drug delivery. The increased interest in oral administration of peptides, as well as poorly soluble and poorly permeable compounds such as drugs for targeted protein degradation, have made permeability a key parameter in oral drug product development. This review describes the various in vitro, in silico and in vivo methodologies that are applied to determine drug permeability in the human gastrointestinal tract and identifies how they are applied in the different stages of drug development. The various methods used to predict, estimate or measure permeability values, ranging from in silico and in vitro methods all the way to studies in animals and humans, are discussed with regard to their advantages, limitations and applications. A special focus is put on novel techniques such as computational approaches, gut-on-chip models and human tissue-based models, where significant progress has been made in the last few years. In addition, the impact of permeability estimations on PK predictions in PBPK modeling, the degree to which excipients can affect drug permeability in clinical studies and the requirements for colonic drug absorption are addressed.

Intestinal organoids as an in vitro platform to characterize disposition, metabolism, and safety profile of small molecules

Intestinal organoids derived from LGR5+ adult stem cells allow for long-term culturing, more closely resemble human physiology than traditional intestinal models, like Caco-2, and have been established for several species. Here we evaluated intestinal organoids for drug disposition, metabolism, and safety applications. Enterocyte-enriched human duodenal organoids were cultured as monolayers to enable bidirectional transport studies. 3D enterocyte-enriched human duodenal and colonic organoids were incubated with probe substrates of major intestinal drug metabolizing enzymes (DMEs). To distinguish human intestinal toxic (high incidence of diarrhea in clinical trials and/or black box warning related to intestinal side effects) from non-intestinal toxic compounds, ATP-based cell viability was used as a readout, and compounds were ranked based on their IC50 values in relation to their 30-times maximal total plasma concentration (Cmax). To assess if rat and dog organoids reproduced the respective in vivo intestinal safety profiles, ATP-based viability was assessed in rat and dog organoids and compared to in vivo intestinal findings when available. Human duodenal monolayers discriminated high and low permeable compounds and demonstrated functional activity for the main efflux transporters Multi drug resistant protein 1 (MDR1, P-glycoprotein P-gp) and Breast cancer resistant protein (BCRP). Human 3D duodenal and colonic organoids also showed metabolic activity for the main intestinal phase I and II DMEs. Organoids derived from specific intestinal segments showed activity differences in line with reported DMEs expression. Undifferentiated human organoids accurately distinguished all but one compound from the test set of non-toxic and toxic drugs. Cytotoxicity in rat and dog organoids correlated with preclinical toxicity findings and observed species sensitivity differences between human, rat, and dog organoids. In conclusion, the data suggest intestinal organoids are suitable in vitro tools for drug disposition, metabolism, and intestinal toxicity endpoints. The possibility to use organoids from different species, and intestinal segment holds great potential for cross-species and regional comparisons.

Optimization of a series of novel, potent and selective Macrocyclic SYK inhibitors

Spleen tyrosine kinase (SYK) is a non-receptor cytoplasmic kinase. Due to its pivotal role in B cell receptor and Fc-receptor signalling, inhibition of SYK has been a target of interest in a variety of diseases. Herein, we report the use of structure-based drug design to discover a series of potent macrocyclic inhibitors of SYK, with excellent kinome selectivity and in vitro metabolic stability. We were able to remove hERG inhibition through the optimization of physical properties, and utilized a pro-drug strategy to address permeability challenges.

Chitosan-Based Thermogelling System for Nose-to-Brain Donepezil Delivery: Optimising Formulation Properties and Nasal Deposition Profile

Donepezil nasal delivery strategies are being continuously investigated for advancing therapy in Alzheimer's disease. The aim of this study was to develop a chitosan-based, donepezil-loaded thermogelling formulation tailored to meet all the requirements for efficient nose-to-brain delivery. A statistical design of the experiments was implemented for the optimisation of the formulation and/or administration parameters, with regard to formulation viscosity, gelling and spray properties, as well as its targeted nasal deposition within the 3D-printed nasal cavity model. The optimised formulation was further characterised in terms of stability, in vitro release, in vitro biocompatibility and permeability (using Calu-3 cells), ex vivo mucoadhesion (using porcine nasal mucosa), and in vivo irritability (using slug mucosal irritation assay). The applied research design resulted in the development of a sprayable donepezil delivery platform characterised by instant gelation at 34 °C and olfactory deposition reaching a remarkably high 71.8% of the applied dose. The optimised formulation showed prolonged drug release (t_1/2 about 90 min), mucoadhesive behaviour, and reversible permeation enhancement, with a 20-fold increase in adhesion and a 1.5-fold increase in the apparent permeability coefficient in relation to the corresponding donepezil solution. The slug mucosal irritation assay demonstrated an acceptable irritability profile, indicating its potential for safe nasal delivery. It can be concluded that the developed thermogelling formulation showed great promise as an efficient donepezil brain-targeted delivery system. Furthermore, the formulation is worth investigating in vivo for final feasibility confirmation.

Physiologically Based Biopharmaceutics Modeling of regional and colon absorption in humans

Colon absorption is a key determinant for successful development of extended release and colon targeted drug products. This is the first systematic evaluation of the ability to predict in vivo regional differences in absorption and the extent of colon absorption in humans using mechanistic physiologically based biopharmaceutics modeling (PBBM). A new dataset, consisting of 19 drugs with a wide range of biopharmaceutics properties and extent of colon absorption in humans, was established. Mechanistic predictions of the extent of absorption and plasma exposure after oral, or jejunal and direct colon administration were performed in GastroPlus and GI-Sim using an a priori approach. Two new colon models developed in GI-Sim, were also evaluated to assess if the prediction performance could be improved. Both GastroPlus and GI-Sim met the pre-defined criteria for accurate predictions of regional and colon absorption for high permeability drugs irrespective of formulation type, while the prediction performance was poor for low permeability drugs. For solutions, the two new GI-Sim colon models improved the colon absorption prediction performance for the low permeability drugs while maintaining the accurate prediction performance for the high permeability drugs. In contrast, the prediction performance decreased for non-solutions using the two new colon models. In conclusion, PBBM can be used with sufficient accuracy to predict regional and colon absorption in humans for high permeability drugs in candidate selection as well as early design and development of extended release or colon targeted drug products. The prediction performance of the current models needs to be improved to allow high accuracy predictions for commercial drug product applications including highly accurate predictions of the entire plasma concentration-time profiles as well as for low permeability drugs.

Discovery of Clinical Candidate AZD0095, a Selective Inhibitor of Monocarboxylate Transporter 4 (MCT4) for Oncology

Due to increased reliance on glycolysis, which produces lactate, monocarboxylate transporters (MCTs) are often upregulated in cancer. MCT4 is associated with the export of lactic acid from cancer cells under hypoxia, so inhibition of MCT4 may lead to cytotoxic levels of intracellular lactate. In addition, tumor-derived lactate is known to be immunosuppressive, so MCT4 inhibition may be of interest for immuno-oncology. At the outset, no potent and selective MCT4 inhibitors had been reported, but a screen identified a triazolopyrimidine hit, with no close structural analogues. Minor modifications to the triazolopyrimidine were made, alongside design of a constrained linker and broad SAR exploration of the biaryl tail to improve potency, physical properties, PK, and hERG. The resulting clinical candidate 15 (AZD0095) has excellent potency (1.3 nM), MCT1 selectivity (>1000×), secondary pharmacology, clean mechanism of action, suitable properties for oral administration in the clinic, and good preclinical efficacy in combination with cediranib.

Designing Selective Drug-like Molecular Glues for the Glucocorticoid Receptor/14-3-3 Protein-Protein Interaction

The ubiquitously expressed glucocorticoid receptor (GR) is a nuclear receptor that controls a broad range of biological processes and is activated by steroidal glucocorticoids such as hydrocortisone or dexamethasone. Glucocorticoids are used to treat a wide variety of conditions, from inflammation to cancer but suffer from a range of side effects that motivate the search for safer GR modulators. GR is also regulated outside the steroid-binding site through protein-protein interactions (PPIs) with 14-3-3 adapter proteins. Manipulation of these PPIs will provide insights into noncanonical GR signaling as well as a new level of control over GR activity. We report the first molecular glues that selectively stabilize the 14-3-3/GR PPI using the related nuclear receptor estrogen receptor α (ERα) as a selectivity target to drive design. These 14-3-3/GR PPI stabilizers can be used to dissect noncanonical GR signaling and enable the development of novel atypical GR modulators.

Synthesis, In Silico and In Vivo Toxicity Assessment of Functionalized Pyridophenanthridinones via Sequential MW-Assisted Intramolecular Friedel-Crafts Alkylation and Direct C-H Arylation

A rapid, efficient, and original synthesis of novel pyrido[3,2,1-de]phenanthridin-6-ones is reported. First, the key cinnamamide intermediates 8a-f were easily prepared from commercial substituted anilines, cinnamic acid, and 2-bromobenzylbromide in a tandem amidation and N-alkylation protocol. Then, these N-aryl-N-(2-bromobenzyl) cinnamamides 8a-f were subjected to a TFA-mediated intramolecular Friedel-Crafts alkylation followed by a Pd-catalyzed direct C-H arylation to obtain a series of potentially bioactive 4-phenyl-4,5-dihydro-6H,8H-pyrido[3,2,1-de]phenanthridin-6-one derivatives 4a-f in good yields. Finally, the toxicological profile of the prepared final compounds, including their corresponding intermediates, was explored through in silico computational methods, while the acute toxicity toward zebrafish embryos (96 hpf-LC₅₀, 50% lethal concentration) was also determined in the present study.

Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches

The heterogeneity of the Caco-2 cell line and differences in experimental protocols for permeability assessment using this cell-based method have resulted in the high variability of Caco-2 permeability measurements. These problems have limited the generation of large datasets to develop accurate and applicable regression models. This study presents a QSPR approach developed on the KNIME analytical platform and based on a structurally diverse dataset of over 4900 molecules. Interpretable models were obtained using random forest supervised recursive algorithms for data cleaning and feature selection. The development of a conditional consensus model based on regional and global regression random forest produced models with RMSE values between 0.43–0.51 for all validation sets. The potential applicability of the model as a surrogate for the in vitro Caco-2 assay was demonstrated through blind prediction of 32 drugs recommended by the International Council for the Harmonization of Technical Requirements for Pharmaceuticals (ICH) for validation of in vitro permeability methods. The model was validated for the preliminary estimation of the BCS/BDDCS class. The KNIME workflow developed to automate new drug prediction is freely available. The results suggest that this automated prediction platform is a reliable tool for identifying the most promising compounds with high intestinal permeability during the early stages of drug discovery.

Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure

Animal pharmacokinetic (PK) data as well as human and animal in vitro systems are utilized in drug discovery to define the rate and route of drug elimination. Accurate prediction and mechanistic understanding of drug clearance and disposition in animals provide a degree of confidence for extrapolation to humans. In addition, prediction of in vivo properties can be used to improve design during drug discovery, help select compounds with better properties, and reduce the number of in vivo experiments. In this study, we generated machine learning models able to predict rat in vivo PK parameters and concentration-time PK profiles based on the molecular chemical structure and either measured or predicted in vitro parameters. The models were trained on internal in vivo rat PK data for over 3000 diverse compounds from multiple projects and therapeutic areas, and the predicted endpoints include clearance and oral bioavailability. We compared the performance of various traditional machine learning algorithms and deep learning approaches, including graph convolutional neural networks. The best models for PK parameters achieved R² = 0.63 [root mean squared error (RMSE) = 0.26] for clearance and R² = 0.55 (RMSE = 0.46) for bioavailability. The models provide a fast and cost-efficient way to guide the design of molecules with optimal PK profiles, to enable the prediction of virtual compounds at the point of design, and to drive prioritization of compounds for in vivo assays.

Importance of Binding Site Hydration and Flexibility Revealed When Optimizing a Macrocyclic Inhibitor of the Keap1-Nrf2 Protein-Protein Interaction

Upregulation of the transcription factor Nrf2 by inhibition of the interaction with its negative regulator Keap1 constitutes an opportunity for the treatment of disease caused by oxidative stress. We report a structurally unique series of nanomolar Keap1 inhibitors obtained from a natural product-derived macrocyclic lead. Initial exploration of the structure-activity relationship of the lead, followed by structure-guided optimization, resulted in a 100-fold improvement in inhibitory potency. The macrocyclic core of the nanomolar inhibitors positions three pharmacophore units for productive interactions with key residues of Keap1, including R415, R483, and Y572. Ligand optimization resulted in the displacement of a coordinated water molecule from the Keap1 binding site and a significantly altered thermodynamic profile. In addition, minor reorganizations of R415 and R483 were accompanied by major differences in affinity between ligands. This study therefore indicates the importance of accounting both for the hydration and flexibility of the Keap1 binding site when designing high-affinity ligands.

The role of DMPK science in improving pharmaceutical research and development efficiency

The successful regulatory authority approval rate of drug candidates in the drug development pipeline is crucial for determining pharmaceutical research and development (R&D) efficiency. Regulatory authorities include the US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceutical and Food Safety Bureau Japan (PFSB), among others. Optimal drug metabolism and pharmacokinetics (DMPK) properties influence the progression of a drug candidate from the preclinical to the clinical phase. In this review, we provide a comprehensive assessment of essential concepts, methods, improvements, and challenges in DMPK science and its significance in drug development. This information provides insights into the association of DMPK science with pharmaceutical R&D efficiency.

Discovery and optimization of cyclohexane-1,4-diamines as allosteric MALT1 inhibitors

Inhibition of mucosa-associated lymphoid tissue lymphoma translocation protein-1 (MALT1) is a promising strategy to modulate NF-κB signaling, with the potential to treat B-cell lymphoma and autoimmune diseases. We describe the discovery and optimization of (1s,4s)-N,N'-diaryl cyclohexane-1,4-diamines, a novel series of allosteric MALT1 inhibitors, resulting in compound 8 with single digit micromolar cell potency. X-ray analysis confirms that this compound binds to an induced allosteric site in MALT1. Compound 8 is highly selective and has an excellent in vivo rat PK profile with low clearance and high oral bioavailability, making it a promising lead for further optimization.

Measuring the oral bioavailability of protein hydrolysates derived from food sources: A critical review of current bioassays

BACKGROUND

Food proteins are a source of hydrolysates with potentially useful biological attributes. Bioactive peptides from food-derived proteins are released from hydrolysates using exogenous industrial processes or endogenous intestinal enzymes. Current in vitro permeability assays have limitations in predicting the oral bioavailability (BA) of bioactive peptides in humans. There are also difficulties in relating the low blood levels of food-derived bioactive peptides detected in preclinical in vivo models to pharmacodynamic read-outs relevant for humans.

SCOPE AND APPROACH

In this review, we describe in vitro assays of digestion, permeation, and metabolism as indirect predictors of the potential oral BA of hydrolysates and their constituent bioactive peptides. We discuss the relationship between industrial hydrolysis processes and the oral BA of hydrolysates and their peptide by-products.

KEY FINDINGS

Hydrolysates are challenging for analytical detection methods due to capacity for enzymatic generation of peptides with novel sequences and also new modifications of these peptides during digestion. Mass spectrometry and peptidomics can improve the capacity to detect individual peptides released from complex hydrolysates in biological milieu.

In Vitro Assessment of the Drug-Drug Interaction Potential of Verinurad and Its Metabolites as Substrates and Inhibitors of Metabolizing Enzymes and Drug Transporters

Verinurad is a selective uric acid transporter 1 (URAT1) inhibitor in development for the treatment of chronic kidney disease and heart failure. In humans, two major acyl glucuronide metabolites have been identified: direct glucuronide M1 and N-oxide glucuronide M8. Using in vitro systems recommended by regulatory agencies, we evaluated the interactions of verinurad, M1, and M8 with major drug-metabolizing enzymes and transporters and the potential for clinically relevant drug-drug interactions (DDIs). The IC50 for inhibition of CYP2C8, CYP2C9, and CYP3A4/5 for verinurad was ≥14.5 µM, and maximum free plasma concentration (Iu,max)/IC50 was <0.02 at the anticipated therapeutic Cmax and therefore not considered a DDI risk. Verinurad was not an inducer of CYP1A2, CYP2B6, or CYP3A4/5. Verinurad was identified as a substrate of the hepatic uptake transporter organic anion-transporting polypeptide (OATP) 1B3. Since verinurad hepatic uptake involved both active and passive transport, there is a low risk of clinically relevant DDIs with OATP, and further study is warranted. Verinurad was a substrate of the efflux transporters P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), and renal transporter organic anion transporter 1 (OAT1), although it is not considered a DDI risk in vivo because of dose-proportional pharmacokinetics (P-gp and BCRP) and limited renal excretion of verinurad (OAT1). M1 and M8 were substrates of multidrug resistance-associated protein (MRP) 2 and MRP4 and inhibitors of MRP2. Apart from verinurad being a substrate of OATP1B3 in vitro, the potential for clinically relevant DDIs involving verinurad and its metabolites as victims or perpetrators of metabolizing enzymes or drug transporters is considered low. SIGNIFICANCE STATEMENT: Drug transporters and metabolizing enzymes have an important role in the absorption and disposition of a drug and its metabolites. Using in vitro systems recommended by regulatory agencies, we determined that, apart from verinurad being a substrate of organic anion-transporting polypeptide 1B3, the potential for clinically relevant drug-drug interactions involving verinurad and its metabolites M1 and M8 as victims or perpetrators of metabolizing enzymes or drug transporters is considered low.

Do Small Molecules Activate the TrkB Receptor in the Same Manner as BDNF? Limitations of Published TrkB Low Molecular Agonists and Screening for Novel TrkB Orthosteric Agonists

TrkB is a tyrosine kinase receptor that is activated upon binding to brain-derived neurotrophic factor (BDNF). To date, the search for low-molecular-weight molecules mimicking BDNF’s action has been unsuccessful. Several molecules exerting antidepressive effects in vivo, such as 7,8-DHF, have been suggested to be TrkB agonists. However, more recent publications question this hypothesis. In this study, we developed a set of experimental procedures including the evaluation of direct interactions, dimerization, downstream signaling, and cytoprotection in parallel with physicochemical and ADME methods to verify the pharmacology of 7,8-DHF and other potential reference compounds, and perform screening for novel TrkB agonists. 7,8 DHF bound to TrkB with K_d = 1.3 μM; however, we were not able to observe any other activity against the TrkB receptor in SN56 T48 and differentiated SH-SY5Y cell lines. Moreover, the pharmacokinetic and pharmacodynamic effects of 7,8-DHF at doses of 1 and 50 mg/kg were examined in mice after i.v and oral administration, respectively. The poor pharmacokinetic properties and lack of observed activation of TrkB-dependent signaling in the brain confirmed that 7,8-DHF is not a relevant tool for studying TrkB activation in vivo. The binding profile for 133 molecular targets revealed a significant lack of selectivity of 7,8-DHF, suggesting a distinct functional profile independent of interaction with TrkB. Additionally, a compound library was screened in search of novel low-molecular-weight orthosteric TrkB agonists; however, we were not able to identify reliable drug candidates. Our results suggest that published reference compounds including 7,8-DHF do not activate TrkB, consistent with canonical dogma, which indicates that the reported pharmacological activity of these compounds should be interpreted carefully in a broad functional context.

Measuring barrier function in organ-on-chips with cleanroom-free integration of multiplexable electrodes

Transepithelial/transendothelial electrical resistance (TEER) measurements can be applied in organ-on-chips (OoCs) to estimate the barrier properties of a tissue or cell layer in a continuous, non-invasive, and label-free manner. Assessing the barrier integrity in in vitro models is valuable for studying and developing barrier targeting drugs. Several systems for measuring the TEER have been shown, but each of them having their own drawbacks. This article presents a cleanroom-free fabrication method for the integration of platinum electrodes in a polydimethylsiloxane OoC, allowing the real-time assessment of the barrier function by employing impedance spectroscopy. The proposed method and electrode arrangement allow visual inspection of the cells cultured in the device at the site of the electrodes, and multiplexing of both the electrodes in one OoC and the number of OoCs in one device. The effectiveness of our system is demonstrated by lining the OoC with intestinal epithelial cells, creating a gut-on-chip, where we monitored the formation, as well as the disruption and recovery of the cell barrier during a 21 day culture period. The application is further expanded by creating a blood-brain-barrier, to show that the proposed fabrication method can be applied to monitor the barrier formation in the OoC for different types of biological barriers.

Matrix Metalloproteinase 13 Inhibitors for Modulation of Osteoclastogenesis: Enhancement of Solubility and Stability

Matrix metalloproteinase 13 (MMP-13) activity has been correlated to breast cancer bone metastasis. It has been proposed that MMP-13 contributes to bone metastasis through the promotion of osteoclastogenesis. To explore the mechanisms of MMP-13 action, we previously described a highly efficacious and selective MMP-13 inhibitor, RF036. Unfortunately, further pursuit of RF036 as a probe of MMP-13 in vitro and in vivo activities was not practical due to the limited solubility and stability of the inhibitor. Our new study has explored replacing the RF036 backbone sulfur atom and terminal methyl group to create inhibitors with more favorable pharmacokinetic properties. One compound, designated inhibitor 3, in which the backbone sulfur and terminal methyl group of RF036 were replaced by nitrogen and oxetane, respectively, had comparable activity, selectivity, and membrane permeability to RF036, while exhibiting greatly enhanced solubility and stability. Inhibitor 3 effectively inhibited MMP-13-mediated osteoclastogenesis but spared collagenolysis, and thus represents a next-generation MMP-13 probe applicable for in vivo studies of breast cancer metastasis.

Drug Disposition in the Lower Gastrointestinal Tract: Targeting and Monitoring

The increasing prevalence of colonic diseases calls for a better understanding of the various colonic drug absorption barriers of colon-targeted formulations, and for reliable in vitro tools that accurately predict local drug disposition. In vivo relevant incubation conditions have been shown to better capture the composition of the limited colonic fluid and have resulted in relevant degradation and dissolution kinetics of drugs and formulations. Furthermore, drug hurdles such as efflux transporters and metabolising enzymes, and the presence of mucus and microbiome are slowly integrated into drug stability- and permeation assays. Traditionally, the well characterized Caco-2 cell line and the Ussing chamber technique are used to assess the absorption characteristics of small drug molecules. Recently, various stem cell-derived intestinal systems have emerged, closely mimicking epithelial physiology. Models that can assess microbiome-mediated drug metabolism or enable coculturing of gut microbiome with epithelial cells are also increasingly explored. Here we provide a comprehensive overview of the colonic physiology in relation to drug absorption, and review colon-targeting formulation strategies and in vitro tools to characterize colonic drug disposition.

Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

As expenditure on drug development increases exponentially, the overall drug discovery process requires a sustainable revolution. Since artificial intelligence (AI) is leading the fourth industrial revolution, AI can be considered as a viable solution for unstable drug research and development. Generally, AI is applied to fields with sufficient data such as computer vision and natural language processing, but there are many efforts to revolutionize the existing drug discovery process by applying AI. This review provides a comprehensive, organized summary of the recent research trends in AI-guided drug discovery process including target identification, hit identification, ADMET prediction, lead optimization, and drug repositioning. The main data sources in each field are also summarized in this review. In addition, an in-depth analysis of the remaining challenges and limitations will be provided, and proposals for promising future directions in each of the aforementioned areas.

Mining Natural Products for Macrocycles to Drug Difficult Targets

Lead generation for difficult-to-drug targets that have large, featureless, and highly lipophilic or highly polar and/or flexible binding sites is highly challenging. Here, we describe how cores of macrocyclic natural products can serve as a high-quality in silico screening library that provides leads for difficult-to-drug targets. Two iterative rounds of docking of a carefully selected set of natural-product-derived cores led to the discovery of an uncharged macrocyclic inhibitor of the Keap1-Nrf2 protein–protein interaction, a particularly challenging target due to its highly polar binding site. The inhibitor displays cellular efficacy and is well-positioned for further optimization based on the structure of its complex with Keap1 and synthetic access. We believe that our work will spur interest in using macrocyclic cores for in silico-based lead generation and also inspire the design of future macrocycle screening collections.

Transport Properties of Statins by Organic Anion Transporting Polypeptide 1A2 and Regulation by Transforming Growth Factor-β Signaling in Human Endothelial Cells

Our in vivo rodent studies have shown that organic anion transporting polypeptide (Oatp) 1a4 is critical for blood-to-brain transport of statins, drugs that are effective neuroprotectants. Additionally, transforming growth factor-β (TGF-β) signaling via the activin receptor-like kinase 1 (ALK1) receptor regulates Oatp1a4 functional expression. The human ortholog of Oatp1a4 is OATP1A2. Therefore, the translational significance of our work requires demonstration that OATP1A2 can transport statins and is regulated by TGF-β/ALK1 signaling. Cellular uptake and monolayer permeability of atorvastatin, pravastatin, and rosuvastatin were investigated in vitro using human umbilical vein endothelial cells (HUVECs). Regulation of OATP1A2 by the TGF-β/ALK1 pathway was evaluated using bone morphogenetic protein 9 (BMP-9), a selective ALK1 agonist, and LDN193189, an ALK1 antagonist. We showed that statin accumulation in HUVECs requires OATP1A2-mediated uptake but is also affected by efflux transporters (i.e., P-glycoprotein, breast cancer resistance protein). Absorptive flux (i.e., apical-to-basolateral) for all statins was higher than secretory flux (i.e., basolateral-to-apical) and was decreased by an OATP inhibitor (i.e., estrone-3-sulfate). OATP1A2 protein expression, statin uptake, and cellular monolayer permeability were increased by BMP-9 treatment. This effect was attenuated in the presence of LDN193189. Apical-to-basolateral statin transport across human endothelial cellular monolayers requires functional expression of OATP1A2, which can be controlled by therapeutically targeting TGF-β/ALK1 signaling. Taken together with our previous work, the present data show that OATP-mediated drug transport is a critical mechanism in facilitating neuroprotective drug disposition across endothelial barriers of the blood-brain barrier. SIGNIFICANCE STATEMENT: Transporter data derived from rodent models requires validation in human models. Using human umbilical vein endothelial cells, this study has shown that statin transport is mediated by OATP1A2. Additionally, we demonstrated that OATP1A2 is regulated by transforming growth factor-β/activin receptor-like kinase 1 signaling. This work emphasizes the need to consider endothelial transporter kinetics and regulation during preclinical drug development. Furthermore, our forward-thinking approach can identify effective therapeutics for diseases for which drug development has been challenging (i.e., neurological diseases).

Self-assembled lecithin-chitosan nanoparticles improve the oral bioavailability and alter the pharmacokinetics of raloxifene

In this study, we report the development and evaluation of soy lecithin-chitosan hybrid nanoparticles to improve the oral bioavailability of raloxifene hydrochloride. The nanoparticles were formed by interaction of negatively charged soy lecithin with positively charged chitosan. The ratio of soy lecithin to chitosan was critical for the charge, and hence the size of the nanoparticles. The optimal soy lecithin to chitosan ratio was 20:1 to obtain nanoparticles with particle size of 208 ± 3 nm, a ζ-potential of 36 ± 2 mV and an entrapment efficiency of 73 ± 3%. The nanoparticles were also characterized by differential scanning calorimetry and FT-IR spectrophotometer. In-vitro drug release was assessed using dialysis bag method in pH 7.4 buffer. The drug loaded nanoparticles did not cause significant reduction in the cell viability at low doses. Pharmacokinetic studies in female Wistar rats showed significant improvement (~4.2 folds) in the oral bioavailability of the drug when loaded into nanoparticles. Further, the modified everted gut sac study showed that these nanoparticles are taken up by active endocytic processes in the intestine. The ex-vivo mucoadhesion studies proved that the nanoparticles get bound to the mucus layer of the intestine, which in turn correlates with reduced excretion of the drug in faeces. In conclusion, the proposed nanoparticles appear promising for effective oral delivery of poorly bioavailable drugs like raloxifene hydrochloride.

Application of the Extended Clearance Classification System (ECCS) in Drug Discovery and Development: Selection of Appropriate In Vitro Tools and Clearance Prediction

In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2-3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection. SIGNIFICANCE STATEMENT: Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System-dependent in vitro to in vivo extrapolation for human clearance prediction.

Drug Absorption Parameters Obtained Using the Isolated Perfused Rat Lung Model Are Predictive of Rat In Vivo Lung Absorption

The ex vivo isolated perfused rat lung (IPL) model has been demonstrated to be a useful tool during drug development for studying pulmonary drug absorption. This study aims to investigate the potential use of IPL data to predict rat in vivo lung absorption. Absorption parameters determined from IPL data (ex vivo input parameters) in combination with intravenously determined pharmacokinetic data were used in a biopharmaceutics model to predict experimental rat in vivo plasma concentration-time profiles and lung amount after inhalation of five different inhalation compounds. The performance of simulations using ex vivo input parameters was compared with simulations using in vitro input parameters, to determine whether and to what extent predictability could be improved by using input parameters determined from the more complex ex vivo model. Simulations using ex vivo input parameters were within twofold average difference (AAFE < 2) from experimental in vivo data for all compounds except one. Furthermore, simulations using ex vivo input parameters performed significantly better than simulations using in vitro input parameters in predicting in vivo lung absorption. It could therefore be advantageous to base predictions of drug performance on IPL data rather than on in vitro data during drug development to increase mechanistic understanding of pulmonary drug absorption and to better understand how different substance properties and formulations might affect in vivo behavior of inhalation compounds.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy

BACKGROUND

DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery.

METHODS

The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing.

RESULTS

This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies.

CONCLUSION

Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

The Discovery of 7-Methyl-2-[(7-methyl[1,2,4]triazolo[1,5-a]pyridin-6-yl)amino]-9-(tetrahydro-2H-pyran-4-yl)-7,9-dihydro-8H-purin-8-one (AZD7648), a Potent and Selective DNA-Dependent Protein Kinase (DNA-PK) Inhibitor

DNA-PK is a key component within the DNA damage response, as it is responsible for recognizing and repairing double-strand DNA breaks (DSBs) via non-homologous end joining. Historically it has been challenging to identify inhibitors of the DNA-PK catalytic subunit (DNA-PKcs) with good selectivity versus the structurally related PI3 (lipid) and PI3K-related protein kinases. We screened our corporate collection for DNA-PKcs inhibitors with good PI3 kinase selectivity, identifying compound 1. Optimization focused on further improving selectivity while improving physical and pharmacokinetic properties, notably co-optimization of permeability and metabolic stability, to identify compound 16 (AZD7648). Compound 16 had no significant off-target activity in the protein kinome and only weak activity versus PI3Kα/γ lipid kinases. Monotherapy activity in murine xenograft models was observed, and regressions were observed when combined with inducers of DSBs (doxorubicin or irradiation) or PARP inhibition (olaparib). These data support progression into clinical studies (NCT03907969).

Structure-Based Virtual Screening, Molecular Dynamics and Binding Free Energy Calculations of Hit Candidates as ALK-5 Inhibitors

Activin-like kinase 5 (ALK-5) is involved in the physiopathology of several conditions, such as pancreatic carcinoma, cervical cancer and liver hepatoma. Cellular events that are landmarks of tumorigenesis, such as loss of cell polarity and acquisition of motile properties and mesenchymal phenotype, are associated to deregulated ALK-5 signaling. ALK-5 inhibitors, such as SB505154, GW6604, SD208, and LY2157299, have recently been reported to inhibit ALK-5 autophosphorylation and induce the transcription of matrix genes. Due to their ability to impair cell migration, invasion and metastasis, ALK-5 inhibitors have been explored as worthwhile hits as anticancer agents. This work reports the development of a structure-based virtual screening (SBVS) protocol aimed to prospect promising hits for further studies as novel ALK-5 inhibitors. From a lead-like subset of purchasable compounds, five molecules were identified as putative ALK-5 inhibitors. In addition, molecular dynamics and binding free energy calculations combined with pharmacokinetics and toxicity profiling demonstrated the suitability of these compounds to be further investigated as novel ALK-5 inhibitors.

Anti-HIV and Anti-Hepatitis C Virus Drugs Inhibit P-Glycoprotein Efflux Activity in Caco-2 Cells and Precision-Cut Rat and Human Intestinal Slices

P-glycoprotein (ABCB1), an ATP-binding-cassette efflux transporter, limits intestinal absorption of its substrates and is a common site of drug-drug interactions (DDIs). ABCB1 has been suggested to interact with many antivirals used to treat HIV and/or chronic hepatitis C virus (HCV) infections. Using bidirectional transport experiments in Caco-2 cells and a recently established ex vivo model of accumulation in precision-cut intestinal slices (PCIS) prepared from rat ileum or human jejunum, we evaluated the potential of anti-HIV and anti-HCV antivirals to inhibit intestinal ABCB1. Lopinavir, ritonavir, saquinavir, atazanavir, maraviroc, ledipasvir, and daclatasvir inhibited the efflux of a model ABCB1 substrate, rhodamine 123 (RHD123), in Caco-2 cells and rat-derived PCIS. Lopinavir, ritonavir, saquinavir, and atazanavir also significantly inhibited RHD123 efflux in human-derived PCIS, while possible interindividual variability was observed in the inhibition of intestinal ABCB1 by maraviroc, ledipasvir, and daclatasvir. Abacavir, zidovudine, tenofovir disoproxil fumarate, etravirine, and rilpivirine did not inhibit intestinal ABCB1. In conclusion, using recently established ex vivo methods for measuring drug accumulation in rat- and human-derived PCIS, we have demonstrated that some antivirals have a high potential for DDIs on intestinal ABCB1. Our data help clarify the molecular mechanisms responsible for reported increases in the bioavailability of ABCB1 substrates, including antivirals and drugs prescribed to treat comorbidity. These results could help guide the selection of combination pharmacotherapies and/or suitable dosing schemes for patients infected with HIV and/or HCV.

Intestinal Fish Cell Barrier Model to Assess Transfer of Organic Chemicals in Vitro: An Experimental and Computational Study

We studied the role of the fish intestine as a barrier for organic chemicals using the epithelial barrier model built on the rainbow trout (Oncorhynchus mykiss) intestinal cell line, RTgutGC and the newly developed exposure chamber, TransFEr, specifically designed to work with hydrophobic and volatile chemicals. Testing 11 chemicals with a range of physicochemical properties (logK_OW: 2.2 to 6.3, logHLC: 6.1 to 2.3) and combining the data with a mechanistic kinetic model enabled the determination of dominant processes underlying the transfer experiments and the derivation of robust transfer rates. Against the current assumption in chemical uptake modeling, chemical transfer did not strictly depend on the logK_OW but resulted from chemical-specific intracellular accumulation and biotransformation combined with paracellular and active transport. Modeling also identified that conducting elaborate measurements of the plastic parts, including the polystyrene insert and the PET filter, is unnecessary and that stirring in the TransFEr chamber reduced the stagnant water layers compared to theoretical predictions. Aside from providing insights into chemical uptake via the intestinal epithelium, this system can easily be transferred to other cell-based barrier systems, such as the fish gill or mammalian intestinal models and may improve in vitro-in vivo extrapolation and prediction of chemical bioaccumulation into organisms.

Discovery of the Oral Leukotriene C4 Synthase Inhibitor (1S,2S)-2-({5-[(5-Chloro-2,4-difluorophenyl)(2-fluoro-2-methylpropyl)amino]-3-methoxypyrazin-2-yl}carbonyl)cyclopropanecarboxylic Acid (AZD9898) as a New Treatment for Asthma

While bronchodilators and inhaled corticosteroids are the mainstay of asthma treatment, up to 50% of asthmatics remain uncontrolled. Many studies show that the cysteinyl leukotriene cascade remains highly activated in some asthmatics, even those on high-dose inhaled or oral corticosteroids. Hence, inhibition of the leukotriene C4 synthase (LTC4S) enzyme could provide a new and differentiated core treatment for patients with a highly activated cysteinyl leukotriene cascade. Starting from a screening hit (3), a program to discover oral inhibitors of LTC4S led to (1S,2S)-2-({5-[(5-chloro-2,4-difluorophenyl)(2-fluoro-2-methylpropyl)amino]-3-methoxypyrazin-2-yl}carbonyl)cyclopropanecarboxylic acid (AZD9898) (36), a picomolar LTC4S inhibitor (IC₅₀ = 0.28 nM) with high lipophilic ligand efficiency (LLE = 8.5), which displays nanomolar potency in cells (peripheral blood mononuclear cell, IC_50,free = 6.2 nM) and good in vivo pharmacodynamics in a calcium ionophore-stimulated rat model after oral dosing (in vivo, IC_50,free = 34 nM). Compound 36 mitigates the GABA binding, hepatic toxicity signal, and in vivo toxicology findings of an early lead compound 7 with a human dose predicted to be 30 mg once daily.

Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides opportunities for the discovery and development of innovative drugs. Various machine learning approaches have recently (re)emerged, some of which may be considered instances of domain-specific AI which have been successfully employed for drug discovery and design. This review provides a comprehensive portrayal of these machine learning techniques and of their applications in medicinal chemistry. After introducing the basic principles, alongside some application notes, of the various machine learning algorithms, the current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects. Finally, several challenges and limitations of the current methods are summarized, with a view to potential future directions for AI-assisted drug discovery and design.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Physicochemical QSAR Analysis of Passive Permeability Across Caco-2 Monolayers

Caco-2 cell line is frequently used as a simplified in vitro model of intestinal absorption. In this study, a database of 1366 Caco-2 permeability coefficients (P_e) for 768 diverse drugs and drug-like compounds was compiled from public sources. The collected data represent permeation rates measured at varying experimental conditions (pH from 4.0 to 8.0, and stirring rates from 0 to >1000 rpm) that presumably account for passive diffusion across mucosal epithelium. These data were subjected to multistep nonlinear regression analysis using a minimal set of physicochemical descriptors (octanol-water log D, pKa, hydrogen bonding potential, and molecular size). The model was constructed in a mechanistic manner incorporating the following components: (i) a hydrodynamic equation of size- and charge-specific along with nonspecific diffusion across the paracellular pathway; (ii) transcellular diffusion represented by thermodynamic membrane/water partitioning ratio; (iii) stirring-dependent limit of maximum achievable permeability due to the presence of unstirred water layer. The obtained model demonstrates good accuracy of log P_e predictions with a residual mean square error <0.5 log units for all training and validation sets. Given its robust performance and straightforward interpretation in terms of simple physicochemical properties, the proposed model may serve as a valuable tool to guide drug discovery efforts toward readily absorbable compounds.