Safety Lead Optimization and Candidate Identification: Integrating New Technologies into Decision-Making

1H NMR spectroscopic characterisation of HepG2 cells as a model metabolic system for toxicology studies

The immortalised human hepatocellular HepG2 cell line is commonly used for toxicology studies as an alternative to animal testing due to its characteristic liver-distinctive functions. However, little is known about the baseline metabolic changes within these cells upon toxin exposure. We have applied high-resolution 1H Nuclear Magnetic Resonance (NMR) spectroscopy to characterise the biochemical composition of HepG2 cells at baseline and post-exposure to hydrogen peroxide (H2O2). Metabolic profiles of live cells, cell extracts, and their spent media supernatants were obtained using 1H high-resolution magic angle spinning (HR-MAS) NMR and 1H NMR spectroscopic techniques. Orthogonal partial least squares discriminant analysis (O-PLS-DA) was used to characterise the metabolites that differed between the baseline and H2O2 treated groups. The results showed that H2O2 caused alterations to 10 metabolites, including acetate, glutamate, lipids, phosphocholine, and creatine in the live cells; 25 metabolites, including acetate, alanine, adenosine diphosphate (ADP), aspartate, citrate, creatine, glucose, glutamine, glutathione, and lactate in the cell extracts, and 22 metabolites, including acetate, alanine, formate, glucose, pyruvate, phenylalanine, threonine, tryptophan, tyrosine, and valine in the cell supernatants. At least 10 biochemical pathways associated with these metabolites were disrupted upon toxin exposure, including those involved in energy, lipid, and amino acid metabolism. Our findings illustrate the ability of NMR-based metabolic profiling of immortalised human cells to detect metabolic effects on central metabolism due to toxin exposure. The established data sets will enable more subtle biochemical changes in the HepG2 model cell system to be identified in future toxicity testing.

DrugGym: A testbed for the economics of autonomous drug discovery

Drug discovery is stochastic. The effectiveness of candidate compounds in satisfying design objectives is unknown ahead of time, and the tools used for prioritization-predictive models and assays-are inaccurate and noisy. In a typical discovery campaign, thousands of compounds may be synthesized and tested before design objectives are achieved, with many others ideated but deprioritized. These challenges are well-documented, but assessing potential remedies has been difficult. We introduce DrugGym, a framework for modeling the stochastic process of drug discovery. Emulating biochemical assays with realistic surrogate models, we simulate the progression from weak hits to sub-micromolar leads with viable ADME. We use this testbed to examine how different ideation, scoring, and decision-making strategies impact statistical measures of utility, such as the probability of program success within predefined budgets and the expected costs to achieve target candidate profile (TCP) goals. We also assess the influence of affinity model inaccuracy, chemical creativity, batch size, and multi-step reasoning. Our findings suggest that reducing affinity model inaccuracy from 2 to 0.5 pIC50 units improves budget-constrained success rates tenfold. DrugGym represents a realistic testbed for machine learning methods applied to the hit-to-lead phase. Source code is available at www.drug-gym.org.

Cinnamaldehyde hydrazone derivatives as potential cathepsin B inhibitors: parallel in-vitro investigation in liver and cerebrospinal fluid

The emergence of cathepsins as a potential target for anticancer drugs has led to extensive research in the development of their inhibitors. In the present study, we designed, synthesized, and characterized several cinnamaldehyde schiff bases employing diverse hydrazines, as potential cathepsin B inhibitors. The parallel studies on cathepsin B isolated from liver and cerebrospinal fluid unveiled the significance of the synthesized compounds as cathepsin B inhibitors at nanomolar concentrations. The compound, 7 exhibited the highest inhibition of 83.48 % and 82.96 % with an IC50 value of 0.06 nM and 0.09 nM for liver and cerebrospinal fluid respectively. The inhibitory potential of synthesized compounds has been extremely effective in comparison to previous reports. With the help of molecular docking studies using iGEMDOCK software, we found that the active site -CH2SH group is involved in the case of α-N-benzoyl-D, l-arginine-b-naphthylamide (BANA), curcumin 2, 3, 6, and 7. For toxicity prediction, ADMET studies were conducted and the synthesized compounds emerged to be non-toxic. The results obtained from the in vitro studies were supported with in silico studies. The synthesized cinnamaldehyde schiff bases can be considered promising drug candidates in conditions with elevated cathepsin B levels.

The Current Status and Use of Microphysiological Systems by the Pharmaceutical Industry: The International Consortium for Innovation and Quality Microphysiological Systems Affiliate Survey and Commentary

Microphysiological systems (MPS) are comprised of one or multiple cell types of human or animal origins that mimic the biochemical/electrical/mechanical responses and blood-tissue barrier properties of the cells observed within a complex organ. The goal of incorporating these in vitro systems is to expedite and advance the drug discovery and development paradigm with improved predictive and translational capabilities. Considering the industry need for improved efficiency and the broad challenges of model qualification and acceptance, the International Consortium for Innovation and Quality (IQ) founded an IQ MPS working group in 2014 and Affiliate in 2018. This group connects thought leaders and end users, provides a forum for crosspharma collaboration, and engages with regulators to qualify translationally relevant MPS models. To understand how pharmaceutical companies are using MPS, the IQ MPS Affiliate conducted two surveys in 2019, survey 1, and 2021, survey 2, which differed slightly in the scope of definition of the complex in vitro models under question. The surveys captured demographics, resourcing, rank order for organs of interest, compound modalities tested, and MPS organ-specific questions, including nonclinical species needs and cell types. The major focus of this manuscript is on results from survey 2, where we specifically highlight the context of use for MPS within safety, pharmacology, or absorption, disposition, metabolism, and excretion and discuss considerations for including MPS data in regulatory submissions. In summary, these data provide valuable insights for developers, regulators, and pharma, offering a view into current industry practices and future considerations while highlighting key challenges impacting MPS adoption. SIGNIFICANCE STATEMENT: The application of microphysiological systems (MPS) represents a growing area of interest in the drug discovery and development framework. This study surveyed 20+ pharma companies to understand resourcing, current areas of application, and the key challenges and barriers to internal MPS adoption. These results will provide regulators, tech providers, and pharma industry leaders a starting point to assess the current state of MPS applications along with key learnings to effectively realize the potential of MPS as an emerging technology.

Hepatic Models in Precision Medicine: An African Perspective on Pharmacovigilance

Pharmaceuticals are indispensable to healthcare as the burgeoning global population is challenged by diseases. The African continent harbors unparalleled genetic diversity, yet remains largely underrepresented in pharmaceutical research and development, which has serious implications for pharmaceuticals approved for use within the African population. Adverse drug reactions (ADRs) are often underpinned by unique variations in genes encoding the enzymes responsible for their uptake, metabolism, and clearance. As an example, individuals of African descent (14–34%) harbor an exclusive genetic variant in the gene encoding a liver metabolizing enzyme (CYP2D6) which reduces the efficacy of the breast cancer chemotherapeutic Tamoxifen. However, CYP2D6 genotyping is not required prior to dispensing Tamoxifen in sub-Saharan Africa. Pharmacogenomics is fundamental to precision medicine and the absence of its implementation suggests that Africa has, to date, been largely excluded from the global narrative around stratified healthcare. Models which could address this need, include primary human hepatocytes, immortalized hepatic cell lines, and induced pluripotent stem cell (iPSC) derived hepatocyte-like cells. Of these, iPSCs, are promising as a functional in vitro model for the empirical evaluation of drug metabolism. The scale with which pharmaceutically relevant African genetic variants can be stratified, the expediency with which these platforms can be established, and their subsequent sustainability suggest that they will have an important role to play in the democratization of stratified healthcare in Africa. Here we discuss the requirement for African hepatic models, and their implications for the future of pharmacovigilance on the African continent.

LightBBB: computational prediction model of blood-brain-barrier penetration based on LightGBM

MOTIVATION

Identification of blood-brain barrier (BBB) permeability of a compound is a major challenge in neurotherapeutic drug discovery. Conventional approaches for BBB permeability measurement are expensive, time-consuming and labor-intensive. BBB permeability is associated with diverse chemical properties of compounds. However, BBB permeability prediction models have been developed using small datasets and limited features, which are usually not practical due to their low coverage of chemical diversity of compounds. Aim of this study is to develop a BBB permeability prediction model using a large dataset for practical applications. This model can be used for facilitated compound screening in the early stage of brain drug discovery.

RESULTS

A dataset of 7162 compounds with BBB permeability (5453 BBB+ and 1709 BBB-) was compiled from the literature, where BBB+ and BBB- denote BBB-permeable and non-permeable compounds, respectively. We trained a machine learning model based on Light Gradient Boosting Machine (LightGBM) algorithm and achieved an overall accuracy of 89%, an area under the curve (AUC) of 0.93, specificity of 0.77 and sensitivity of 0.93, when 10-fold cross-validation was performed. The model was further evaluated using 74 central nerve system compounds (39 BBB+ and 35 BBB-) obtained from the literature and showed an accuracy of 90%, sensitivity of 0.85 and specificity of 0.94. Our model outperforms over existing BBB permeability prediction models.

AVAILABILITYAND IMPLEMENTATION

The prediction server is available at http://ssbio.cau.ac.kr/software/bbb.

Rapid Screening and Quantification of Multi-Class Multi-Residue Veterinary Drugs in Pork by a Modified Quechers Protocol Coupled to UPLC-QOrbitrap HRMS

Background:

A rapid and simple analytical method for the screening and quantification of multi-residues was established by a quick, easy, cheap, effective, rugged and safe (QuEChERS) approach coupled to ultra-performance liquid chromatography and electrospray ionization quadrupole orbitrap high-resolution mass spectrometry (UPLC-Q-Orbitrap HRMS). A total number of 59 veterinary drugs were investigated, which belonged to 12 classes, such as β-agonist, quinolones, sulfonamides, tetracyclines, lincomycin series, triphenylmethane, nitroimidazoles, macrolides, amide alcohols, quinoxalines, steroid hormone and sedatives.

Methods:

The factors which influence the determination of veterinary drugs residues, such as mobile phase, extract solvent, clean up sorbent, and re-dissolved solvent, were optimized by the single factor experiment. The method was sufficiently validated by using the parameters of linearity, sensitivity, accuracy, and repeatability.

Results:

The response of the detector was linear for 59 veterinary drug residues in extensive range (two to three orders of magnitude) with a high coefficient of determination (R2) (0.9995-0.9998). The limit of quantification (LOQ) ranged from 0.1μg/kg to 2.0μg/kg for 59 veterinary drug residues in pork samples. The repeatability was in the range of 1.0%-9.5%. Average recoveries of 59 veterinary drugs at three spiked levels ranged from 53.7%-117.8% with relative standard deviation (RSD) of 1.9%-13.9%. The full MS scan coupled with data-dependent MS/MS mode was applied for screening the target compounds to simultaneously obtain the accurate mass of parent ion and the mass spectrum of fragments. Elemental composition, accurate mass, and retention time and characteristic fragment ions were used to establish a homemade database.

Conclusion:

The ability of the homemade database was verified by analyzing the real pork samples, and the result was satisfactory.

Neurotropic activity and safety of methylene-cycloalkylacetate (MCA) derivative 3-(3-allyl-2-methylenecyclohexyl) propanoic acid

Polyneuropathy is a disease involving multiple peripheral nerves injuries. Axon regrowth remains the major prerequisite for plasticity, regeneration, circuit formation, and eventually functional recovery and therefore, regulation of neurite outgrowth might be a candidate for treating polyneuropathies. In a recent study, we synthesized and established the methylene-cycloalkylacetate (MCAs) pharmacophore as a lead for the development of a neurotropic drug (inducing neurite/axonal outgrowth) using the PC12 neuronal model. In the present study we extended the characterizations of the in vitro neurotropic effect of the derivative 3-(3-allyl-2-methylenecyclohexyl) propanoic acid (MCA-13) on dorsal root ganglia and spinal cord neuronal cultures and analyzed its safety properties using blood biochemistry and cell counting, acute toxicity evaluation in mice and different in vitro "off-target" pharmacological evaluations. This MCA derivative deserves further preclinical mechanistic pharmacological characterizations including therapeutic efficacy in in vivo animal models of polyneuropathies, toward development of a clinically relevant neurotropic drug.

[Strategic assessment for nonclinical safety in drug discovery]

Given that safety (toxicity) liabilities in drug development still account for a large proportion of development discontinuations and market withdrawals, establishing an appropriate safety prediction and evaluation strategy is an important topic. In particular, discontinuation in the late stage of development following large investment has a significant impact. Accurate safety assessment in the early preclinical stage is therefore highly desirable. However, pre-GLP (exploratory) safety evaluation is not subject to regulatory guidelines, and structure and practices accordingly vary widely among companies. Against this background, it can be difficult for non-safety researchers to understand why a particular evaluation/assay system and study design have been selected and tested, and why these differ from those in other companies. This article introduces the background to and concept of a revised strategy for exploratory safety assessment at Astellas, and explains that exploratory safety assessment is not uniform but varies with strategy.

Bioactivation of diclofenac in human hepatocytes and the proposed human hepatic proteins modified by reactive metabolites

To reveal putative bioactivation pathways of diclofenac, in vitro human liver materials such as microsomal fractions and hepatocytes were used to confirm metabolic activation of diclofenac by ³⁵S-cysteine trapping assay and covalent binding assay. Candidate human liver proteins possibly targeted by ¹⁴C-diclofenac via bioactivation were investigated using two-dimensional gel electrophoresis followed by detection of remaining radioactivity on the modified proteins with bio-imaging analyzer.In the ³⁵S-cysteine trapping assay, three and two adducts with ³⁵S-cysteine were observed in NADPH-fortified and UDPGA-fortified human liver microsomes, respectively. In the covalent binding assay using ¹⁴C-diclofenac in human hepatocytes, the extent of covalent binding of diclofenac to human hepatic proteins increased time-dependently. Addition of glutathione attenuated the extent of covalent binding of ¹⁴C-diclofenac to human liver microsomal proteins.Fifty-nine proteins from human hepatocytes were proposed as the candidate proteins targeted by reactive metabolites of diclofenac. Proteins modified by cytochrome P450-mediated reactive metabolites were identified by using a cytochrome P450 inhibitor, 1-aminobenzyltriazole and seven of the nine radioactive protein spots were removed by 1-aminobenzyltriazole treatment.In contrast, the remaining two radioactive protein spots, mainly containing human serum albumin and heat shock proteins, were not affected by the addition of 1-aminobenzyltriazole, which suggested the involvement of the acyl glucuronide of diclofenac, formed via uridine diphosphate-glucuronosyl transferases, in the covalent modifications induced by diclofenac.

Roughened graphite biointerfaced with P450 liver microsomes: Surface and electrochemical characterizations

Low-cost, voltage-driven biocatalytic designs for rapid drug metabolism assay, chemical toxicity screening, and pollutant biosensing represent considerable significance for pharmaceutical, biomedical, and environmental applications. In this study, we have designed biointerfaces of human liver microsomes with various roughened, high-purity graphite disk electrodes to study electrochemical and electrocatalytic properties. Successful spectral and microscopic characterizations, direct bioelectronic communication, direct electron-transfer rates from the electrode to liver microsomal enzymes, microsomal heme-enzyme specific oxygen reduction currents, and voltage-driven diclofenac hydroxylation (chosen as the probe reaction) are presented.

Safety Considerations in the Development of Hippo Pathway Inhibitors in Cancers

The Hippo pathway is a critical regulator of cell and organ growth and has emerged as a target for therapeutic intervention in cancers. Its signaling is thought to play an important role in various physiological processes including homeostasis and tissue regeneration. To date there has been limited information about potential pharmacology-related (on-target) safety liabilities of Hippo pathway inhibitors in the context of cancer indications. Herein, we review data from human genetic disorders and genetically engineered rodent models to gain insight into safety liabilities that may emerge from the inhibition of Hippo pathway. Germline systemic deletion of murine Hippo pathway effectors (Yap, Taz, and Teads) resulted in embryonic lethality or developmental phenotypes. Mouse models with tissue-specific deletion (or mutant overexpression) of the key effectors in Hippo pathways have indicated that, at least in some tissues, Hippo signaling may be dispensable for physiological homeostasis; and appears to be critical for regeneration upon tissue damage, indicating that patients with underlying comorbidities and/or insults caused by therapeutic agents and/or comedications may have a higher risk. Caution should be taken in interpreting phenotypes from tissue-specific transgenic animal models since some tissue-specific promoters are turned on during development. In addition, therapeutic agents may result in systemic effects not well-predicted by animal models with tissue-specific gene deletion. Therefore, the development of models that allows for systemic deletion of Yap and/or Taz in adult animals will be key in evaluating the potential safety liabilities of Hippo pathway modulation. In this review, we focus on potential challenges and strategies for targeting the Hippo pathway in cancers.

The human endogenous metabolome as a pharmacology baseline for drug discovery

We have limited understanding of the variation in in vitro affinities of drugs for their targets. An analysis of a highly curated set of 815 interactions between 566 drugs and 129 primary targets reveals that 71% of drug-target affinities have values above that of the corresponding endogenous ligand, 96% of them fitting within a range of two orders of magnitude. Our findings suggest that the evolutionary optimised affinity of endogenous ligands for their native proteins can serve as a baseline for the primary pharmacology of drugs. We show that the degree of off-target selectivity and safety risks of drugs derived from their secondary pharmacology depend very much on that baseline. Thus, we propose a new approach for estimating safety margins.

In Silico Prediction of Blood-Brain Barrier Permeability of Compounds by Machine Learning and Resampling Methods

The blood-brain barrier (BBB) as a part of absorption protects the central nervous system by separating the brain tissue from the bloodstream. In recent years, BBB permeability has become a critical issue in chemical ADMET prediction, but almost all models were built using imbalanced data sets, which caused a high false-positive rate. Therefore, we tried to solve the problem of biased data sets and built a reliable classification model with 2358 compounds. Machine learning and resampling methods were used simultaneously for the refinement of models with both 2 D molecular descriptors and molecular fingerprints to represent the chemicals. Through a series of evaluation, we realized that resampling methods such as Synthetic Minority Oversampling Technique (SMOTE) and SMOTE+edited nearest neighbor could effectively solve the problem of imbalanced data sets and that MACCS fingerprint combined with support vector machine performed the best. After the final construction of a consensus model, the overall accuracy rate was increased to 0.966 for the final external data set. Also, the accuracy rate of the model for the test set was 0.919, with an excellent balanced capacity of 0.925 (sensitivity) to predict BBB-positive compounds and of 0.899 (specificity) to predict BBB-negative compounds. Compared with other BBB classification models, our models reduced the rate of false positives and were more robust in prediction of BBB-positive as well as BBB-negative compounds, which would be quite helpful in early drug discovery.

A rapid analytical method to quantify complex organohalogen contaminant mixtures in large samples of high lipid mammalian tissues

In vitro investigations of the health impact of individual chemical compounds have traditionally been used in risk assessments. However, humans and wildlife are exposed to a plethora of potentially harmful chemicals, including organohalogen contaminants (OHCs). An alternative exposure approach to individual or simple mixtures of synthetic OHCs is to isolate the complex mixture present in free-ranging wildlife, often non-destructively sampled from lipid rich adipose. High concentration stock volumes required for in vitro investigations do, however, pose a great analytical challenge to extract sufficient amounts of complex OHC cocktails. Here we describe a novel method to easily, rapidly and efficiently extract an environmentally accumulated and therefore relevant contaminant cocktail from large (10-50 g) marine mammal blubber samples. We demonstrate that lipid freeze-filtration with acetonitrile removes up to 97% of blubber lipids, with minimal effect on the efficiency of OHC recovery. Sample extracts after freeze-filtration were further processed to remove residual trace lipids via high-pressure gel permeation chromatography and solid phase extraction. Average recoveries of OHCs from triplicate analysis of killer whale (Orcinus orca), polar bear (Ursus maritimus) and pilot whale (Globicephala spp.) blubber standard reference material (NIST SRM-1945) ranged from 68 to 80%, 54-92% and 58-145%, respectively, for ¹³C-enriched internal standards of six polychlorinated biphenyl congeners, 16 organochlorine pesticides and four brominated flame retardants. This approach to rapidly generate OHC mixtures shows great potential for experimental exposures using complex contaminant mixtures, research or monitoring driven contaminant quantification in biological samples, as well as the untargeted identification of emerging contaminants.

Current nonclinical testing paradigms in support of safe clinical trials: An IQ Consortium DruSafe perspective

The transition from nonclinical to First-in-Human (FIH) testing is one of the most challenging steps in drug development. In response to serious outcomes in a recent Phase 1 trial (sponsored by Bial), IQ Consortium/DruSafe member companies reviewed their nonclinical approach to progress small molecules safely to FIH trials. As a common practice, safety evaluation begins with target selection and continues through iterative in silico and in vitro screening to identify molecules with increased probability of acceptable in vivo safety profiles. High attrition routinely occurs during this phase. In vivo exploratory and pivotal FIH-enabling toxicity studies are then conducted to identify molecules with a favorable benefit-risk profile for humans. The recent serious incident has reemphasized the importance of nonclinical testing plans that are customized to the target, the molecule, and the intended clinical plan. Despite the challenges and inherent risks of transitioning from nonclinical to clinical testing, Phase 1 studies have a remarkably good safety record. Given the rapid scientific evolution of safety evaluation, testing paradigms and regulatory guidance must evolve with emerging science. The authors posit that the practices described herein, together with science-based risk assessment and management, support safe FIH trials while advancing development of important new medicines.

What can nanosafety learn from drug development? The feasibility of "safety by design"

"Safety by design" (SbD) is an intuitively appealing concept that is on the rise within nanotoxicology and nanosafety research, as well as within nanotechnology research policy. It leans on principles established within drug discovery and development (DDD) and seeks to address safety early, as well as throughout product development. However, it remains unclear what the concept of SbD exactly entails for engineered nanomaterials (ENMs) or how it is envisioned to be implemented. Here, we review the concept as it is emerging in European research and compare its resemblance with the safety testing and assessment practices in DDD. From this comparison, it is clear that "safety" is not obtained through DDD, and that SbD should be considered a starting point rather than an end, meaning that products will still need to progress through thorough safety evaluations and regulation. We conclude that although risk reduction is clearly desirable, the way SbD is currently communicated tends to treat safety as an inherent material property and that this is fundamentally problematic as it represents a recasting and reduction of societal issues into technical problems. SbD therefore faces a multitude of challenges, from practical implementation to unrealistic stakeholder expectations.