Reducing safety-related drug attrition: the use of in vitro pharmacological profiling

Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing

New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.

Thieno[2,3-d]pyrimidine-Based Positive Allosteric Modulators of Human Mas-Related G Protein-Coupled Receptor X1 (MRGPRX1)

Mas-related G protein-coupled receptor X1 (MRGPRX1) is a human sensory neuron-specific receptor and potential target for the treatment of pain. Positive allosteric modulators (PAMs) of MRGPRX1 have the potential to preferentially activate the receptors at the central terminals of primary sensory neurons and minimize itch side effects caused by peripheral activation. Using a high-throughput screening (HTS) hit, a series of thieno[2,3-d]pyrimidine-based molecules were synthesized and evaluated as human MRGPRX1 PAMs in HEK293 cells stably transfected with human MrgprX1 gene. An iterative process to improve potency and metabolic stability led to the discovery of orally available 6-(tert-butyl)-5-(3,4-dichlorophenyl)-4-(2-(trifluoromethoxy)phenoxy)thieno[2,3-d]pyrimidine (1t), which can be distributed to the spinal cord, the presumed site of action, following oral administration. In a neuropathic pain model induced by sciatic nerve chronic constriction injury (CCI), compound 1t (100 mg/kg, po) reduced behavioral heat hypersensitivity in humanized MRGPRX1 mice, demonstrating the therapeutic potential of MRGPRX1 PAMs in treating neuropathic pain.

GPCR Systems Pharmacology: A Different Perspective on the Development of Biased Therapeutics

G protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors and are the target of approximately one-third of all Food and Drug Administration (FDA)-approved pharmaceutical drugs. GPCRs interact with many transducers, such as heterotrimeric G proteins, GPCR kinases (GRKs), and β-arrestins. Recent experiments have demonstrated that some ligands can activate distinct effector proteins over others, a phenomenon termed biased agonism. These discoveries have raised the potential of developing drugs which preferentially activate therapeutic signaling pathways over those that lead to deleterious side effects. However, to date, only one biased GPCR therapeutic has received FDA approval and many others have either failed to meet their specified primary endpoints and or demonstrate superiority over currently available treatments. Additionally, there is a lack of understanding regarding how biased agonism measured at a GPCR leads to specific downstream physiologic responses. Here, we briefly summarize the history and current status of biased agonism at GPCRs and suggest adoption of a systems pharmacology approach upon which to develop GPCR-targeted drugs that demonstrate heightened therapeutic efficacy with improved side effect profiles.

Pharmacological targeting of MTHFD2 suppresses acute myeloid leukemia by inducing thymidine depletion and replication stress

The folate metabolism enzyme MTHFD2 (methylenetetrahydrofolate dehydrogenase/cyclohydrolase) is consistently overexpressed in cancer but its roles are not fully characterized, and current candidate inhibitors have limited potency for clinical development. In the present study, we demonstrate a role for MTHFD2 in DNA replication and genomic stability in cancer cells, and perform a drug screen to identify potent and selective nanomolar MTHFD2 inhibitors; protein cocrystal structures demonstrated binding to the active site of MTHFD2 and target engagement. MTHFD2 inhibitors reduced replication fork speed and induced replication stress followed by S-phase arrest and apoptosis of acute myeloid leukemia cells in vitro and in vivo, with a therapeutic window spanning four orders of magnitude compared with nontumorigenic cells. Mechanistically, MTHFD2 inhibitors prevented thymidine production leading to misincorporation of uracil into DNA and replication stress. Overall, these results demonstrate a functional link between MTHFD2-dependent cancer metabolism and replication stress that can be exploited therapeutically with this new class of inhibitors.

Free Drug Theory - No Longer Just a Hypothesis?

The Free Drug Hypothesis is a well-established concept within the scientific lexicon pervading many areas of Drug Discovery and Development, and yet it is poorly defined by virtue of many variations appearing in the literature. Clearly, unbound drug is in dynamic equilibrium with respect to absorption, distribution, metabolism, elimination, and indeed, interaction with the desired pharmacological target. Binding interactions be they specific (e.g. high affinity) or nonspecific (e.g. lower affinity/higher capacity) are governed by the same fundamental physicochemical tenets including Hill-Langmuir Isotherms, the Law of Mass Action and Drug Receptor Theory. With this in mind, it is time to recognise a more coherent version and consider it the Free Drug Theory and a hypothesis no longer. Today, we have the experimental and modelling capabilities, pharmacological knowledge, and an improved understanding of unbound drug distribution (e.g. Kp_uu) to raise the bar on our understanding and analysis of experimental data. The burden of proof should be to rule out mechanistic possibilities and/or experimental error before jumping to the conclusion that any observations contradict these fundamentals.

Optimization of TAM16, a Benzofuran That Inhibits the Thioesterase Activity of Pks13; Evaluation toward a Preclinical Candidate for a Novel Antituberculosis Clinical Target

With increasing drug resistance in tuberculosis (TB) patient populations, there is an urgent need for new drugs. Ideally, new agents should work through novel targets so that they are unencumbered by preexisting clinical resistance to current treatments. Benzofuran 1 was identified as a potential lead for TB inhibiting a novel target, the thioesterase domain of Pks13. Although, having promising activity against Mycobacterium tuberculosis, its main liability was inhibition of the hERG cardiac ion channel. This article describes the optimization of the series toward a preclinical candidate. Despite improvements in the hERG liability in vitro, when new compounds were assessed in ex vivo cardiotoxicity models, they still induced cardiac irregularities. Further series development was stopped because of concerns around an insufficient safety window. However, the demonstration of in vivo activity for multiple series members further validates Pks13 as an attractive novel target for antitubercular drugs and supports development of alternative chemotypes.

Polypharmacology: The science of multi-targeting molecules

Polypharmacology is a concept where a molecule can interact with two or more targets simultaneously. It offers many advantages as compared to the conventional single-targeting molecules. A multi-targeting drug is much more efficacious due to its cumulative efficacy at all of its individual targets making it much more effective in complex and multifactorial diseases like cancer, where multiple proteins and pathways are involved in the onset and development of the disease. For a molecule to be polypharmacologic in nature, it needs to possess promiscuity which is the ability to interact with multiple targets; and at the same time avoid binding to antitargets which would otherwise result in off-target adverse effects. There are certain structural features and physicochemical properties which when present would help researchers to predict if the designed molecule would possess promiscuity or not. Promiscuity can also be identified via advanced state-of-the-art computational methods. In this review, we also elaborate on the methods by which one can intentionally incorporate promiscuity in their molecules and make them polypharmacologic. The polypharmacology paradigm of "one drug-multiple targets" has numerous applications especially in drug repurposing where an already established drug is redeveloped for a new indication. Though designing a polypharmacological drug is much more difficult than designing a single-targeting drug, with the current technologies and information regarding different diseases and chemical functional groups, it is plausible for researchers to intentionally design a polypharmacological drug and unlock its advantages.

Increasing the Value of Data Within a Large Pharmaceutical Company Through In Silico Models

The present contribution describes how in silico models and methods are applied at different stages of the drug discovery process in the pharmaceutical industry. A description of the most relevant computational methods and tools is given along with an evaluation of their performance in the assessment of potential genotoxic impurities and the prediction of off-target in vitro pharmacology. The challenges of predicting the outcome of highly complex in vivo studies are discussed followed by considerations on how novel ways to manage, store, exchange, and analyze data may advance knowledge and facilitate modeling efforts. In this context, the current status of broad data sharing initiatives, namely, eTOX and eTransafe, will be described along with related projects that could significantly reduce the use of animals in drug discovery in the future.

OUP accepted manuscript

The content of this article derives from a Health and Environmental Sciences Institute (HESI) consortium with a focus to improve cardiac safety during drug development. A detailed literature review was conducted to evaluate the concordance between nonclinical repolarization assays and the clinical thorough QT (TQT) study. Food and Drug Administration and HESI developed a joint database of nonclinical and clinical data, and a retrospective analysis of 150 anonymized drug candidates was reviewed to compare the performance of 3 standard nonclinical assays with clinical TQT study findings as well as investigate mechanism(s) potentially responsible for apparent discrepancies identified. The nonclinical assays were functional (I_Kr) current block (Human ether-a-go-go related gene), action potential duration, and corrected QT interval in animals (in vivo corrected QT). Although these nonclinical assays demonstrated good specificity for predicting negative clinical QT prolongation, they had relatively poor sensitivity for predicting positive clinical QT prolongation. After review, 28 discordant TQT-positive drugs were identified. This article provides an overview of direct and indirect mechanisms responsible for QT prolongation and theoretical reasons for lack of concordance between clinical TQT studies and nonclinical assays. We examine 6 specific and discordant TQT-positive drugs as case examples. These were derived from the unique HESI/Food and Drug Administration database. We would like to emphasize some reasons for discordant data including, insufficient or inadequate nonclinical data, effects of the drug on other cardiac ion channels, and indirect and/or nonelectrophysiological effects of drugs, including altered heart rate. We also outline best practices that were developed based upon our evaluation.

Synthesis and Pharmacological Characterization of Visabron, a Backbone Cyclic Peptide Dual Antagonist of α4β1 (VLA-4)/α9β1 Integrin for Therapy of Multiple Sclerosis

Integrins α4β1/ α9β1 are important in the pathogenesis and progression of inflammatory and autoimmune diseases by their roles in leukocyte activation and trafficking. Natalizumab, a monoclonal antibody selectively targeting α4β1 integrin and blocking leukocyte trafficking to the central nervous system, is an immunotherapy for multiple sclerosis (MS). However, due to its adverse effects associated with chronic treatment, alternative strategies using small peptide mimetic inhibitors are being sought. In the present study, we synthesized and characterized visabron c (4-4), a backbone cyclic octapeptide based on the sequence TMLD, a non-RGD unique α4β1 integrin recognition sequence motif derived from visabres, a proteinous disintegrin from the viper venom. Visabron c (4-4) was selected from a minilibrary with conformational diversity based on its potency and selectivity in functional adhesion cellular assays. Visabron c (4-4)'s serum stability, pharmacokinetics, and therapeutic effects following ip injection were assessed in an experimental autoimmune encephalomyelitis (EAE) animal model. Furthermore, visabron c (4-4)'s lack of toxic effects in mice was verified by blood analysis, tissue pathology, immunogenicity, and "off-target" effects, indicating its significant tolerability and lack of immunogenicity. Visabron c (4-4) can be delivered systemically. The in vitro and in vivo data justify visabron c (4-4) as a safe alternative peptidomimetic lead compound/drug to monoclonal anti-α4 integrin antibodies, steroids, and other immunosuppressant drugs. Moreover, visabron c (4-4) design may pave the way for developing new therapies for a variety of other inflammatory and/or autoimmune diseases.

The rapidly evolving role of cryo-EM in drug design

Since the early 2010s, cryo-electron microscopy (cryo-EM) has evolved to a mainstream structural biology method in what has been dubbed the "resolution revolution". Pharma companies also began to use cryo-EM in drug discovery, evidenced by a growing number of industry publications. Hitherto limited in resolution, throughput and attainable molecular weight, cryo-EM is rapidly overcoming its main limitations for more widespread use through a new wave of technological advances. This review discusses how cryo-EM has already impacted drug discovery, and how the state-of-the-art is poised to further revolutionize its application to previously intractable proteins as well as new use cases.

Efficacy and safety of next-generation tick transcriptome-derived direct thrombin inhibitors

Despite their limitations, unfractionated heparin (UFH) and bivalirudin remain standard-of-care parenteral anticoagulants for percutaneous coronary intervention (PCI). We discovered novel direct thrombin inhibitors (DTIs) from tick salivary transcriptomes and optimised their pharmacologic activity. The most potent, ultravariegin, inhibits thrombin with a K_i of 4.0 pM, 445-fold better than bivalirudin. Unexpectedly, despite their greater antithrombotic effect, variegin/ultravariegin demonstrated less bleeding, achieving a 3-to-7-fold wider therapeutic index in rodent thrombosis and bleeding models. When used in combination with aspirin and ticagrelor in a porcine model, variegin/ultravariegin reduced stent thrombosis compared with antiplatelet therapy alone but achieved a 5-to-7-fold lower bleeding time than UFH/bivalirudin. Moreover, two antibodies screened from a naïve human antibody library effectively reversed the anticoagulant activity of ultravariegin, demonstrating proof-of-principle for antidote reversal. Variegin and ultravariegin are promising translational candidates for next-generation DTIs that may reduce peri-PCI bleeding in the presence of antiplatelet therapy.

Neuronal population models reveal specific linear conductance controllers sufficient to rescue preclinical disease phenotypes

Preclinical drug candidates are screened for their ability to ameliorate in vitro neuronal electrophysiology, and go/no-go decisions progress drugs to clinical trials based on population means across cells and animals. However, these measures do not mitigate clinical endpoint risk. Population-based modeling captures variability across multiple electrophysiological measures from healthy, disease, and drug phenotypes. We pursued optimizing therapeutic targets by identifying coherent sets of ion channel target modulations for recovering heterogeneous wild-type (WT) population excitability profiles from a heterogeneous Huntington's disease (HD) population. Our approach combines mechanistic simulations with population modeling of striatal neurons using evolutionary optimization algorithms to design 'virtual drugs'. We introduce efficacy metrics to score populations and rank virtual drug candidates. We found virtual drugs using heuristic approaches that performed better than single target modulators and standard classification methods. We compare a real drug to virtual candidates and demonstrate a novel in silico triaging method.

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors

Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster, and help patients complying with their treatments. Accelerated pharmaceutical development and drug product approval rates can further benefit from the quantum computing (QC) technology, which will ultimately enable larger profits from patent-protected market exclusivity.Key pharma stakeholders are endorsing cutting-edge technologies based on AI and QC , covering drug discovery, preclinical and clinical development, and postapproval activities. Indeed, AI-QC applications are expected to become standard in the pharma operating model over the next 5-10 years. Generalizing scalability to larger pharmaceutical problems instead of specialization is now the main principle for transforming pharmaceutical tasks on multiple fronts, for which systematic and cost-effective solutions have benefited in areas such as molecular screening, synthetic pathway design, and drug discovery and development.The information generated by coupling the life cycle of drugs and AI and/or QC through data-driven analysis, neural network prediction, and chemical system monitoring will enable (1) better understanding of the complexity of process data, (2) streamlining the design of experiments, (3) discovering new molecular targets and materials, and also (4) planning or rethinking upcoming pharmaceutical challenges The power of AI-QC makes accessible a range of different pharmaceutical problems and their rationalization that have not been previously addressed due to a lack of appropriate analytical tools, demonstrating the breadth of potential applications of these emerging multidimensional approaches. In this context, creating the right AI-QC strategy often involves a steep learning path, especially given the embryonic stage of the industry development and the relative lack of case studies documenting success. As such, a comprehensive knowledge of the underlying pillars is imperative to extend the landscape of applications across the drug life cycle.The topics enclosed in this chapter will focus on AI-QC methods applied to drug discovery and development, with emphasis on the most recent advances in this field.

In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Optimization of TopoIV Potency, ADMET Properties, and hERG Inhibition of 5-Amino-1,3-dioxane-Linked Novel Bacterial Topoisomerase Inhibitors: Identification of a Lead with In Vivo Efficacy against MRSA

Novel bacterial topoisomerase inhibitors (NBTIs) are among the most promising new antibiotics in preclinical/clinical development. We previously reported dioxane-linked NBTIs with potent antistaphylococcal activity and reduced hERG inhibition, a key safety liability. Herein, polarity-focused optimization enabled the delineation of clear structure-property relationships for both microsomal metabolic stability and hERG inhibition, resulting in the identification of lead compound 79. This molecule demonstrates potent antibacterial activity against diverse Gram-positive pathogens, inhibition of both DNA gyrase and topoisomerase IV, a low frequency of resistance, a favorable in vitro cardiovascular safety profile, and in vivo efficacy in a murine model of methicillin-resistant Staphylococcus aureus infection.

Peripherally active dextromethorphan derivatives lower blood glucose levels by targeting pancreatic islets

Dextromethorphan (DXM) acts as cough suppressant via its central action. Cell-protective effects of this drug have been reported in peripheral tissues, making DXM potentially useful for treatment of several common human diseases, such as type 2 diabetes mellitus (T2DM). Pancreatic islets are among the peripheral tissues that positively respond to DXM, and anti-diabetic effects of DXM were observed in two placebo-controlled, randomized clinical trials in humans with T2DM. Since these effects were associated with central side effects, we here developed chemical derivatives of DXM that pass the blood-brain barrier to a significantly lower extent than the original drug. We show that basic nitrogen-containing residues block central adverse events of DXM without reducing its anti-diabetic effects, including the protection of human pancreatic islets from cell death. These results show how to chemically modify DXM, and possibly other morphinans, as to exclude central side effects, while targeting peripheral tissues, such as pancreatic islets.

Strategies to apply 3Rs in preclinical testing

Animal experimentation has been fundamental in biological and biomedical research. To guarantee the maximum quality, efficacy and/or safety of products intended for the use in humans in vivo testing is necessary; however, for over 60 years, alternative methods have been developed in response to the necessity to reduce the number of animals used in experimentation, to guarantee their welfare; resorting to animal models only when strictly necessary. The three Rs (Replacement, Reduction, and Refinement), seek to ensure the rational and respectful use of laboratory animals and maintain an adequate projection in terms of bioethical considerations. This article describes different approaches to apply 3Rs in preclinical experimentation for either research or regulatory purposes.

Discovery of LYC-55716: A Potent, Selective, and Orally Bioavailable Retinoic Acid Receptor-Related Orphan Receptor-γ (RORγ) Agonist for Use in Treating Cancer

Retinoic acid receptor-related orphan receptor γ (RORc, RORγ, or NR1F3) is the nuclear receptor master transcription factor that drives the function and development of IL-17-producing T helper cells (Th17), cytotoxic T cells (Tc17), and subsets of innate lymphoid cells. Activation of RORγ+ T cells in the tumor microenvironment is hypothesized to render immune infiltrates more effective at countering tumor growth. To test this hypothesis, a family of benzoxazines was optimized to provide LYC-55716 (37c), a potent, selective, and orally bioavailable small-molecule RORγ agonist. LYC-55716 decreases tumor growth and enhances survival in preclinical tumor models and was nominated as a clinical development candidate for evaluation in patients with solid tumors.

Remdesivir and EIDD-1931 Interact with Human Equilibrative Nucleoside Transporters 1 and 2: Implications for Reaching SARS-CoV-2 Viral Sanctuary Sites

Equilibrative nucleoside transporters (ENTs) are present at the blood-testis barrier (BTB), where they can facilitate antiviral drug disposition to eliminate a sanctuary site for viruses detectable in semen. The purpose of this study was to investigate ENT-drug interactions with three nucleoside analogs, remdesivir, molnupiravir, and molnupiravir's active metabolite, β-d-N⁴-hydroxycytidine (EIDD-1931), and four non-nucleoside molecules repurposed as antivirals for coronavirus disease 2019 (COVID-19). The study used three-dimensional pharmacophores for ENT1 and ENT2 substrates and inhibitors and Bayesian machine learning models to identify potential interactions with these transporters. In vitro transport experiments demonstrated that remdesivir was the most potent inhibitor of ENT-mediated [³H]uridine uptake (ENT1 IC₅₀: 39 μM; ENT2 IC₅₀: 77 μM), followed by EIDD-1931 (ENT1 IC₅₀: 259 μM; ENT2 IC₅₀: 467 μM), whereas molnupiravir was a modest inhibitor (ENT1 IC₅₀: 701 μM; ENT2 IC₅₀: 851 μM). Other proposed antivirals failed to inhibit ENT-mediated [³H]uridine uptake below 1 mM. Remdesivir accumulation decreased in the presence of 6-S-[(4-nitrophenyl)methyl]-6-thioinosine (NBMPR) by 30% in ENT1 cells (P = 0.0248) and 27% in ENT2 cells (P = 0.0054). EIDD-1931 accumulation decreased in the presence of NBMPR by 77% in ENT1 cells (P = 0.0463) and by 64% in ENT2 cells (P = 0.0132), which supported computational predictions that both are ENT substrates that may be important for efficacy against COVID-19. NBMPR failed to decrease molnupiravir uptake, suggesting that ENT interaction is likely inhibitory. Our combined computational and in vitro data can be used to identify additional ENT-drug interactions to improve our understanding of drugs that can circumvent the BTB. SIGNIFICANCE STATEMENT: This study identified remdesivir and EIDD-1931 as substrates of equilibrative nucleoside transporters 1 and 2. This provides a potential mechanism for uptake of these drugs into cells and may be important for antiviral potential in the testes and other tissues expressing these transporters.

A Novel CD73 Inhibitor SHR170008 Suppresses Adenosine in Tumor and Enhances Anti-Tumor Activity with PD-1 Blockade in a Mouse Model of Breast Cancer

Introduction

CD73 and adenosine support growth-promoting neovascularization, metastasis, and survival in cells, and promote anti-PD-1 mAb therapy-induced immune escape. Consequently, developing a CD73 inhibitor as monotherapy and a potential beneficial combination partner with immune-checkpoint inhibitors needs investigation.

Methods

CD73 inhibitors were evaluated in vitro with soluble and membrane-bound CD73 enzymes, as well as its PD biomarker responses in human peripheral blood mononuclear cells (PBMC) by flow cytometry and ELISA. The binding modes of the molecules were analyzed via molecular modeling. The anti-tumor activity and synergistic effect of SHR170008 in combination with anti-PD-1 mAb were evaluated in a syngeneic mouse breast cancer model.

Results

SHR170008 was discovered during the initial structural modifications on the link between the ribose and the α-phosphate of AMPCP, which significantly improved the stability of the compound confirmed by the metabolite identification study. Further modifications on the adenine base of AMPCP improved the potency due to forming stronger interactions with CD73 protein. It exhibited potent inhibitory activities on soluble and endogenous membrane-bound CD73 enzymes, and induced IFNγ production, reversed AMP-suppressed CD25⁺ and CD8⁺/CD25⁺ expression, and enhanced granzyme B production on CD8⁺ T cells in human PBMC. SHR170008 showed dose-dependent anti-tumor efficacy with suppression of adenosine in the tumors in EMT6 mouse breast tumor model. The increase of adenosine in tumor tissue by anti-PD-1 mAb alone was suppressed by SHR170008 in the combination groups. Simultaneous inhibition of CD73 and PD-1 neutralization synergistically enhanced antitumor immunity and biomarkers in response, and exposures of SHR170008 were correlated with the efficacy readouts.

Conclusion

Our findings suggest that CD73 may serve as an immune checkpoint by generating adenosine, which suppresses the antitumor activity of anti-PD-1 mAb, and inhibition of CD73 may be a potential beneficial combination partner with immune-checkpoint inhibitors to improve their therapeutic outcomes in general.

Sensing technologies and experimental platforms for the characterization of advanced oral drug delivery systems

Complex and miniaturized oral drug delivery systems are being developed rapidly for targeted, controlled drug release and improved bioavailability. Standard analytical techniques are widely used to characterize i) drug carrier and active pharmaceutical ingredients before loading into a delivery device (to ensure the solid form), and ii) the entire drug delivery system during the development process. However, in light of the complexity and the size of some of these systems, standard techniques as well as novel sensing technologies and experimental platforms need to be used in tandem. These technologies and platforms are discussed in this review, with a special focus on passive delivery systems in size range from a few 100 µm to a few mm. Challenges associated with characterizing these systems and evaluating their effect on oral drug delivery in the preclinical phase are also discussed.

Can preclinical drug development help to predict adverse events in clinical trials?

The development of novel therapeutics is associated with high rates of attrition, with unexpected adverse events being a major cause of failure. Serious adverse events have led to organ failure, cancer development and deaths that were not expected outcomes in clinical trials. These life-threatening events were not identified during therapeutic development due to the lack of preclinical safety tests that faithfully represented human physiology. We highlight the successful application of several novel technologies, including high-throughput screening, organs-on-chips, microbiome-containing drug-testing platforms and humanised mouse models, for mechanistic studies and prediction of toxicity. We propose the incorporation of similar preclinical tests into future drug development to reduce the likelihood of hazardous therapeutics entering later-stage clinical trials.

MTADV 5-MER peptide suppresses chronic inflammations as well as autoimmune pathologies and unveils a new potential target-Serum Amyloid A

Despite the existence of potent anti-inflammatory biological drugs e.g., anti-TNF and anti IL-6 receptor antibodies, for treating chronic inflammatory and autoimmune diseases, these are costly and not specific. Cheaper oral available drugs remain an unmet need. Expression of the acute phase protein Serum Amyloid A (SAA) is dependent on release of pro-inflammatory cytokines IL-1, IL-6 and TNF-α during inflammation. Conversely, SAA induces pro-inflammatory cytokine secretion, including Th17, leading to a pathogenic vicious cycle and chronic inflammation. 5- MER peptide (5-MP) MTADV (methionine-threonine-alanine-aspartic acid-valine), also called Amilo-5MER, was originally derived from a sequence of a pro-inflammatory CD44 variant isolated from synovial fluid of a Rheumatoid Arthritis (RA) patient. This human peptide displays an efficient anti-inflammatory effects to ameliorate pathology and clinical symptoms in mouse models of RA, Inflammatory Bowel Disease (IBD) and Multiple Sclerosis (MS). Bioinformatics and qRT-PCR revealed that 5-MP, administrated to encephalomyelytic mice, up-regulates genes contributing to chronic inflammation resistance. Mass spectrometry of proteins that were pulled down from an RA synovial cell extract with biotinylated 5-MP, showed that it binds SAA. 5-MP disrupted SAA assembly, which is correlated with its pro-inflammatory activity. The peptide MTADV (but not scrambled TMVAD) significantly inhibited the release of pro-inflammatory cytokines IL-6 and IL-1β from SAA-activated human fibroblasts, THP-1 monocytes and peripheral blood mononuclear cells. 5-MP suppresses the pro-inflammatory IL-6 release from SAA-activated cells, but not from non-activated cells. 5-MP could not display therapeutic activity in rats, which are SAA deficient, but does inhibit inflammations in animal models of IBD and MS, both are SAA-dependent, as shown by others in SAA knockout mice. In conclusion, 5-MP suppresses chronic inflammation in animal models of RA, IBD and MS, which are SAA-dependent, but not in animal models, which are SAA-independent.

Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients

Next generation risk assessment (NGRA) is an exposure-led, hypothesis-driven approach that has the potential to support animal-free safety decision-making. However, significant effort is needed to develop and test the in vitro and in silico (computational) approaches that underpin NGRA to enable confident application in a regulatory context. A workshop was held in Montreal in 2019 to discuss where effort needs to be focussed and to agree on the steps needed to ensure safety decisions made on cosmetic ingredients are robust and protective. Workshop participants explored whether NGRA for cosmetic ingredients can be protective of human health, and reviewed examples of NGRA for cosmetic ingredients. From the limited examples available, it is clear that NGRA is still in its infancy, and further case studies are needed to determine whether safety decisions are sufficiently protective and not overly conservative. Seven areas were identified to help progress application of NGRA, including further investments in case studies that elaborate on scenarios frequently encountered by industry and regulators, including those where a ‘high risk’ conclusion would be expected. These will provide confidence that the tools and approaches can reliably discern differing levels of risk. Furthermore, frameworks to guide performance and reporting should be developed.

A proteomic platform to identify off-target proteins associated with therapeutic modalities that induce protein degradation or gene silencing

Novel modalities such as PROTAC and RNAi have the ability to inadvertently alter the abundance of endogenous proteins. Currently available in vitro secondary pharmacology assays, which evaluate off-target binding or activity of small molecules, do not fully assess the off-target effects of PROTAC and are not applicable to RNAi. To address this gap, we developed a proteomics-based platform to comprehensively evaluate the abundance of off-target proteins. First, we selected off-target proteins using genetics and pharmacology evidence. This process yielded 2813 proteins, which we refer to as the “selected off-target proteome” (SOTP). An iterative algorithm was then used to identify four human cell lines out of 932. The 4 cell lines collectively expressed ~ 80% of the SOTP based on transcriptome data. Second, we used mass spectrometry to quantify the intracellular and extracellular proteins from the selected cell lines. Among over 10,000 quantifiable proteins identified, 1828 were part of the predefined SOTP. The SOTP was designed to be easily modified or expanded, owing to the rational selection process developed and the label free LC–MS/MS approach chosen. This versatility inherent to our platform is essential to design fit-for-purpose studies that can address the dynamic questions faced in investigative toxicology.

Optimization of the Urea Linker of Triazolopyridazine MMV665917 Results in a New Anticryptosporidial Lead with Improved Potency and Predicted hERG Safety Margin

Cryptosporidiosis is caused by infection of the small intestine by Cryptosporidium parasites, resulting in severe diarrhea, dehydration, malabsorption, and potentially death. The only FDA-approved therapeutic is only partially effective in young children and ineffective for immunocompromised patients. Triazolopyridazine MMV665917 is a previously reported anti-Cryptosporidium screening hit with in vivo efficacy but suffers from modest inhibition of the hERG ion channel, which could portend cardiotoxicity. Herein, we describe our initial development of structure-activity relationships of this novel lead series with a particular focus on optimization of the piperazine-urea linker. We have discovered that piperazine-acetamide is a superior linker resulting in identification of SLU-2633, which has an EC₅₀ of 0.17 μM, an improved projected margin versus hERG, prolonged pharmacokinetic exposure in small intestine, and oral efficacy in vivo with minimal systemic exposure. SLU-2633 represents a significant advancement toward the identification of a new effective and safe treatment for cryptosporidiosis.

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.

Effects of nicotinic acetylcholine receptor-activating alkaloids on anxiety-like behavior in zebrafish

Alkaloids are a structurally complex group of natural products that have a diverse range of biological activities and significant therapeutic applications. In this study, we examined the acute, anxiolytic-like effects of nicotinic acetylcholine receptor (nAChR)-activating alkaloids with reported neuropharmacological effects but whose effects on anxiety are less well understood. Because α4β2 nAChRs can regulate anxiety, we first demonstrated the functional activities of alkaloids on these receptors in vitro. Their effects on anxiety-like behavior in zebrafish were then examined using the zebrafish novel tank test (NTT). The NTT is a relatively high-throughput behavioral paradigm that takes advantage of the natural tendency of fish to dive down when stressed or anxious. We report for the first time that cotinine, anatabine, and methylanatabine may suppress this anxiety-driven zebrafish behavior after a single 20-min treatment. Effective concentrations of these alkaloids were well above the concentrations naturally found in plants and the concentrations needed to induce anxiolytic-like effect by nicotine. These alkaloids showed good receptor interactions at the α4β2 nAChR agonist site as demonstrated by in vitro binding and in silico docking model, although somewhat weaker than that for nicotine. Minimal or no significant effect of other compounds may have been due to low bioavailability of these compounds in the brain, which is supported by the in silico prediction of blood–brain barrier permeability. Taken together, our findings indicate that nicotine, although not risk-free, is the most potent anxiolytic-like alkaloid tested in this study, and other natural alkaloids may regulate anxiety as well.

NITD-688, a pan-serotype inhibitor of the dengue virus NS4B protein, shows favorable pharmacokinetics and efficacy in preclinical animal models

Dengue virus (DENV) is a mosquito-borne flavivirus that poses a threat to public health, yet no antiviral drug is available. We performed a high-throughput phenotypic screen using the Novartis compound library and identified candidate chemical inhibitors of DENV. This chemical series was optimized to improve properties such as anti-DENV potency and solubility. The lead compound, NITD-688, showed strong potency against all four serotypes of DENV and demonstrated excellent oral efficacy in infected AG129 mice. There was a 1.44-log reduction in viremia when mice were treated orally at 30 milligrams per kilogram twice daily for 3 days starting at the time of infection. NITD-688 treatment also resulted in a 1.16-log reduction in viremia when mice were treated 48 hours after infection. Selection of resistance mutations and binding studies with recombinant proteins indicated that the nonstructural protein 4B is the target of NITD-688. Pharmacokinetic studies in rats and dogs showed a long elimination half-life and good oral bioavailability. Extensive in vitro safety profiling along with exploratory rat and dog toxicology studies showed that NITD-688 was well tolerated after 7-day repeat dosing, demonstrating that NITD-688 may be a promising preclinical candidate for the treatment of dengue.

Genome-wide CRISPR/Cas9 screening in human iPS derived cardiomyocytes uncovers novel mediators of doxorubicin cardiotoxicity

Human induced pluripotent stem (iPS) cell technologies coupled with genetic engineering now facilitate the study of the molecular underpinnings of disease in relevant human cell types. Application of CRISPR/Cas9-based approaches for genome-scale functional screening in iPS-derived cells, however, has been limited by technical constraints, including inefficient transduction in pooled format, loss of library representation, and poor cellular differentiation. Herein, we present optimized approaches for whole-genome CRISPR/Cas9 based screening in human iPS derived cardiomyocytes with near genome-wide representation at both the iPS and differentiated cell stages. As proof-of-concept, we perform a screen to investigate mechanisms underlying doxorubicin mediated cell death in iPS derived cardiomyocytes. We identified two poorly characterized, human-specific transporters (SLCO1A2, SLCO1B3) whose loss of function protects against doxorubicin-cardiotoxicity, but does not affect cell death in cancer cells. This study provides a technical framework for genome-wide functional screening in iPS derived cells and identifies new targets to mitigate doxorubicin-cardiotoxicity in humans.

Aggregation and analysis of secondary pharmacology data from investigational new drug submissions at the US Food and Drug Administration

Secondary pharmacology studies are utilized by the pharmaceutical industry as a cost-efficient tool to identify potential safety liabilities of drugs before entering Phase 1 clinical trials. These studies are recommended by the Food and Drug Administration (FDA) as a part of the Investigational New Drug (IND) application. However, despite the utility of these assays, there is little guidance on which targets should be screened and which format should be used. Here, we evaluated 226 secondary pharmacology profiles obtained from close to 90 unique sponsors. The results indicated that the most tested target in our set was the GABA benzodiazepine receptor (tested 168 times), the most hit target was adenosine 3 (hit 24 times), and the target with the highest hit percentage was the quinone reductase 2 (NQO2) receptor (hit 29% of the time). The overall results were largely consistent with those observed in previous publications. However, this study also identified the need for improvement in the submission process of secondary pharmacology studies by industry, which could enhance their utility for regulatory purpose. FDA-industry collaborative working groups will utilize this data to determine the best methods for regulatory submission of these studies and evaluate the need for a standard target panel.

Repolarization instability and arrhythmia by IKr block in single human-induced pluripotent stem cell-derived cardiomyocytes and 2D monolayers

Aims

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have proven valuable for studies in drug discovery and safety, although limitations regarding their structural and electrophysiological characteristics persist. In this study, we investigated the electrophysiological properties of Pluricyte^® CMs, a commercially available hiPSC-CMs line with a ventricular phenotype, and assessed arrhythmia incidence by I_Kr block at the single-cell and 2D monolayer level.

Methods and results

Action potentials were measured at different pacing frequencies, using dynamic clamp. Through voltage-clamp experiments, we determined the properties of I_Na, I_Kr, and I_CaL. Intracellular Ca²⁺ measurements included Ca²⁺-transients at baseline and during caffeine perfusion. Effects of I_Kr block were assessed in single hiPSC-CMs and 2D monolayers (multi-electrode arrays). Action-potential duration (APD) and its rate dependence in Pluricyte^® CMs were comparable to those reported for native human CMs. I_Na, I_Kr, and I_CaL revealed amplitudes, kinetics, and voltage dependence of activation/inactivation similar to other hiPSC-CM lines and, to some extent, to native CMs. Near-physiological Ca²⁺-induced Ca²⁺ release, response to caffeine and excitation–contraction coupling gain characterized the cellular Ca²⁺-handling. Dofetilide prolonged the APD and field-potential duration, and induced early afterdepolarizations. Beat-to-beat variability of repolarization duration increased significantly before the first arrhythmic events in single Pluricyte^® CMs and 2D monolayers, and predicted pending arrhythmias better than action-potential prolongation.

Conclusion

Taking their ion-current characteristics and Ca²⁺ handling into account, Pluricyte^® CMs are suitable for in vitro studies on action potentials and field potentials. Beat-to-beat variability of repolarization duration proved useful to evaluate the dynamics of repolarization instability and demonstrated its significance as proarrhythmic marker in hiPSC-CMs during I_Kr block.

Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening

Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.

TEMPORARY REMOVAL: Acute cell stress screen with supervised machine learning predicts cytotoxicity of excipients

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Large scale meta-analysis of preclinical toxicity data for target characterisation and hypotheses generation

Recent technological advances in the field of big data have increased our capabilities to query large databases and combine information from different domains and disciplines. In the area of preclinical studies, initiatives like SEND (Standard for Exchange of Nonclinical Data) will also contribute to collect and present nonclinical data in a consistent manner and increase analytical possibilities. With facilitated access to preclinical data and improvements in analytical algorithms there will surely be an expectation for organisations to ensure all the historical data available to them is leveraged to build new hypotheses. These kinds of analyses may soon become as important as the animal studies themselves, in addition to being critical components to achieve objectives aligned with 3Rs. This article proposes the application of meta-analyses at large scale in corporate databases as a tool to exploit data from both preclinical studies and in vitro pharmacological activity assays to identify associations between targets and tissues that can be used as seeds for the development of causal hypotheses to characterise of targets. A total of 833 in-house preclinical toxicity studies relating to 416 compounds reported to be active (pXC50 ≥ 5.5) against a panel of 96 selected targets of interest for potential off-target non desired effects were meta-analysed, aggregating the data in tissue-target pairs. The primary outcome was the odds ratio (OR) of the number of animals with observed events (any morphology, any severity) in treated and control groups in the tissue analysed. This led to a total of 2139 meta-analyses producing a total of 364 statistically significant associations (random effects model), 121 after adjusting by multiple comparison bias. The results show the utility of the proposed approach to leverage historical corporate data and may offer a vehicle for researchers to share, aggregate and analyse their preclinical toxicological data in precompetitive environments.

Intra- and intercellular signaling pathways associated with drug-induced cardiac pathophysiology

Cardiac physiology and homeostasis are maintained by the interaction of multiple cell types, via both intra- and intercellular signaling pathways. Perturbations in these signaling pathways induced by oncology therapies can reduce cardiac function, ultimately leading to heart failure. As cancer survival increases, related cardiovascular complications are becoming increasingly prevalent, thus identifying the perturbations and cell signaling drivers of cardiotoxicity is increasingly important. Here, we discuss the homotypic and heterotypic cellular interactions that form the basis of intra- and intercellular cardiac signaling pathways, and how oncological agents disrupt these pathways, leading to heart failure. We also highlight the emerging systems biology techniques that can be applied, enabling a deeper understanding of the intra- and intercellular signaling pathways across multiple cell types associated with cardiovascular toxicity.

In Vitro Models for Studying Respiratory Host-Pathogen Interactions

Respiratory diseases and lower respiratory tract infections are among the leading cause of death worldwide and, especially given the recent severe acute respiratory syndrome coronavirus-2 pandemic, are of high and prevalent socio-economic importance. In vitro models, which accurately represent the lung microenvironment, are of increasing significance given the ethical concerns around animal work and the lack of translation to human disease, as well as the lengthy time to market and the attrition rates associated with clinical trials. This review gives an overview of the biological and immunological components involved in regulating the respiratory epithelium system in health, disease, and infection. The evolution from 2D to 3D cell biology and to more advanced technological integrated models for studying respiratory host-pathogen interactions are reviewed and provide a reference point for understanding the in vitro modeling requirements. Finally, the current limitations and future perspectives for advancing this field are presented.

Precision Medicine and cardiac channelopathies: when dreams meet reality

Precision Medicine (PM) is an innovative approach that, by relying on large populations’ datasets, patients’ genetics and characteristics, and advanced technologies, aims at improving risk stratification and at identifying patient-specific management through targeted diagnostic and therapeutic strategies. Cardiac channelopathies are being progressively involved in the evolution brought by PM and some of them are benefiting from these novel approaches, especially the long QT syndrome. Here, we have explored the main layers that should be considered when developing a PM approach for cardiac channelopathies, with a focus on modern in vitro strategies based on patient-specific human-induced pluripotent stem cells and on in silico models. PM is where scientists and clinicians must meet and integrate their expertise to improve medical care in an innovative way but without losing common sense. We have indeed tried to provide the cardiologist’s point of view by comparing state-of-the-art techniques and approaches, including revolutionary discoveries, to current practice. This point matters because the new approaches may, or may not, exceed the efficacy and safety of established therapies. Thus, our own eagerness to implement the most recent translational strategies for cardiac channelopathies must be tempered by an objective assessment to verify whether the PM approaches are indeed making a difference for the patients. We believe that PM may shape the diagnosis and treatment of cardiac channelopathies for years to come. Nonetheless, its potential superiority over standard therapies should be constantly monitored and assessed before translating intellectually rewarding new discoveries into clinical practice.

A property-response perspective on modern toxicity assessment and drug toxicity index (DTI)

Toxicity related failures in drug discovery and clinical development have motivated scientists and regulators to develop a wide range of in-vitro, in-silico tools coupled with data science methods. Older drug discovery rules are being constantly modified to churn out any hidden predictive value. Nonetheless, the dose-response concepts remain central to all these methods. Over the last 2 decades medicinal chemists, and pharmacologists have observed that different physicochemical, and pharmacological properties capture trends in toxic responses. We propose that these observations should be viewed in a comprehensive property-response framework where dose is only a factor that modifies the inherent toxicity potential. We then introduce the recently proposed "Drug Toxicity Index (DTI)" and briefly summarize its applications. A webserver is available to calculate DTI values (https://all-tool-kit.github.io/Web-Tool.html).

Identification of First-in-Class Inhibitors of Kallikrein-Related Peptidase 6 That Promote Oligodendrocyte Differentiation

Multiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system (CNS) that causes severe motor, sensory, and cognitive impairments. Kallikrein-related peptidase (KLK)6 is the most abundant serine protease secreted in the CNS, mainly by oligodendrocytes, the myelin-producing cells of the CNS, and KLK6 is assumed to be a robust biomarker of MS, since it is highly increased in the cerebrospinal fluid (CSF) of MS patients. Here, we report the design and biological evaluation of KLK6's low-molecular-weight inhibitors, para-aminobenzyl derivatives. Interestingly, selected hit compounds were selective of the KLK6 proteolytic network encompassing KLK1 and plasmin that also participate in the development of MS physiopathology. Moreover, hits were found noncytotoxic on primary cultures of murine neurons and oligodendrocyte precursor cells (OPCs). Among them, two compounds (32 and 42) were shown to promote the differentiation of OPCs into mature oligodendrocytes in vitro constituting thus emerging leads for the development of regenerative therapies.

Cold-Start Problems in Data-Driven Prediction of Drug-Drug Interaction Effects

Combining drugs, a phenomenon often referred to as polypharmacy, can induce additional adverse effects. The identification of adverse combinations is a key task in pharmacovigilance. In this context, in silico approaches based on machine learning are promising as they can learn from a limited number of combinations to predict for all. In this work, we identify various subtasks in predicting effects caused by drug–drug interaction. Predicting drug–drug interaction effects for drugs that already exist is very different from predicting outcomes for newly developed drugs, commonly called a cold-start problem. We propose suitable validation schemes for the different subtasks that emerge. These validation schemes are critical to correctly assess the performance. We develop a new model that obtains AUC-ROC =0.843 for the hardest cold-start task up to AUC-ROC =0.957 for the easiest one on the benchmark dataset of Zitnik et al. Finally, we illustrate how our predictions can be used to improve post-market surveillance systems or detect drug–drug interaction effects earlier during drug development.

Discovery of a novel RORγ antagonist with skin-restricted exposure for topical treatment of mild to moderate psoriasis

Clinical success of IL-17/IL-23 pathway biologics for the treatment of moderate to severe psoriasis suggests that targeting RORγt, a master regulator for the proliferation and function of Th17 cells, could be an effective alternative. However, oral RORγ antagonists (VTP43742, TAK828) with high systemic exposure showed toxicity in phase I/II clinical trials and terminated development. To alleviate the potential safety concerns, identifying compounds with skin-restricted exposure amenable for topical use is of great interest. Systematic structure activity relationship study and multi-parameter optimization led to the discovery of a novel RORγ antagonist (SHR168442) with desired properties for a topical drug. It suppressed the transcription of IL-17 gene, leading to reduction of IL-17 cytokine secretion. It showed high exposure in skin, but low in plasma. Topical application of SHR168442 in Vaseline exhibited excellent efficacy in the imiquimod-induced and IL-23-induced psoriasis-like skin inflammation mouse models and correlated with the reduction of Th17 pathway cytokines, IL-6, TNFα and IL-17A. This work demonstrated restricted skin exposure of RORγ antagonist may provide a new topical treatment option as targeted therapeutics for mild to moderate psoriasis patients and may be suitable for the treatment of any other inflammatory disorders that are accessible locally.

Progress toward B-Cell Lymphoma 6 BTB Domain Inhibitors for the Treatment of Diffuse Large B-Cell Lymphoma and Beyond

B-cell lymphoma 6 (BCL6) is a master regulator of germinal center formation that produce antibody-secreting plasma cells and memory B-cells for sustained immune responses. The BTB domain of BCL6 (BCL6^BTB) forms a homodimer that mediates transcriptional repression by recruiting its corepressor proteins to form a biologically functional transcriptional complex. The protein-protein interaction (PPI) between the BCL6^BTB and its corepressors has emerged as a therapeutic target for the treatment of DLBCL and a number of other human cancers. This Perspective provides an overview of recent advances in the development of BCL6^BTB inhibitors from reversible inhibitors, irreversible inhibitors, to BCL6 degraders. Inhibitor design and medicinal chemistry strategies for the development of novel compounds will be provided. The binding mode of new inhibitors to BCL6^BTB are highlighted. Also, the in vitro and in vivo assays used for the evaluation of new compounds will be discussed.

Structural Basis for Pore Blockade of the Human Cardiac Sodium Channel Nav 1.5 by the Antiarrhythmic Drug Quinidine*

Na_v 1.5, the primary voltage-gated Na⁺ (Na_v ) channel in heart, is a major target for class I antiarrhythmic agents. Here we present the cryo-EM structure of full-length human Na_v 1.5 bound to quinidine, a class Ia antiarrhythmic drug, at 3.3 Å resolution. Quinidine is positioned right beneath the selectivity filter in the pore domain and coordinated by residues from repeats I, III, and IV. Pore blockade by quinidine is achieved through both direct obstruction of the ion permeation path and induced rotation of an invariant Tyr residue that tightens the intracellular gate. Structural comparison with a truncated rat Na_v 1.5 in the presence of flecainide, a class Ic agent, reveals distinct binding poses for the two antiarrhythmics within the pore domain. Our work reported here, along with previous studies, reveals the molecular basis for the mechanism of action of class I antiarrhythmic drugs.