Accelerating Drug Development Using Spatial Multi-omics.

SUMMARY: Spatial biology approaches enabled by innovations in imaging biomarker platforms and artificial intelligence-enabled data integration and analysis provide an assessment of patient and disease heterogeneity at ever-increasing resolution. The utility of spatial biology data in accelerating drug programs, however, requires balancing exploratory discovery investigations against scalable and clinically applicable spatial biomarker analysis.

Stability-based approaches in chemoproteomics.

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Drug development and potential targets for Cushing's syndrome.

Cushing's syndrome (CS) is a complex disorder characterized by the excessive secretion of cortisol, with Cushing's disease (CD), particularly associated with pituitary tumors, exhibiting heightened morbidity and mortality. Although transsphenoidal pituitary surgery (TSS) stands as the primary treatment for CD, there is a crucial need to optimize patient prognosis. Current medical therapy serves as an adjunctive measure due to its unsatisfactory efficacy and unpredictable side effects. In this comprehensive review, we delve into recent advances in understanding the pathogenesis of CS and explore therapeutic options by conducting a critical analysis of potential drug targets and candidates. Additionally, we provide an overview of the design strategy employed in previously reported candidates, along with a summary of structure-activity relationship (SAR) analyses and their biological efficacy. This review aims to contribute valuable insights to the evolving landscape of CS research, shedding light on potential avenues for therapeutic development.

Identification of an inhibitory pocket in falcilysin provides a new avenue for malaria drug development.

Identification of new druggable protein targets remains the key challenge in the current antimalarial development efforts. Here we used mass-spectrometry-based cellular thermal shift assay (MS-CETSA) to identify potential targets of several antimalarials and drug candidates. We found that falcilysin (FLN) is a common binding partner for several drug candidates such as MK-4815, MMV000848, and MMV665806 but also interacts with quinoline drugs such as chloroquine and mefloquine. Enzymatic assays showed that these compounds can inhibit FLN proteolytic activity. Their interaction with FLN was explored systematically by isothermal titration calorimetry and X-ray crystallography, revealing a shared hydrophobic pocket in the catalytic chamber of the enzyme. Characterization of transgenic cell lines with lowered FLN expression demonstrated statistically significant increases in susceptibility toward MK-4815, MMV000848, and several quinolines. Importantly, the hydrophobic pocket of FLN appears amenable to inhibition and the structures reported here can guide the development of novel drugs against malaria.

CAT-DTI: cross-attention and Transformer network with domain adaptation for drug-target interaction prediction.

Accurate and efficient prediction of drug-target interaction (DTI) is critical to advance drug development and reduce the cost of drug discovery. Recently, the employment of deep learning methods has enhanced DTI prediction precision and efficacy, but it still encounters several challenges. The first challenge lies in the efficient learning of drug and protein feature representations alongside their interaction features to enhance DTI prediction. Another important challenge is to improve the generalization capability of the DTI model within real-world scenarios. To address these challenges, we propose CAT-DTI, a model based on cross-attention and Transformer, possessing domain adaptation capability. CAT-DTI effectively captures the drug-target interactions while adapting to out-of-distribution data. Specifically, we use a convolution neural network combined with a Transformer to encode the distance relationship between amino acids within protein sequences and employ a cross-attention module to capture the drug-target interaction features. Generalization to new DTI prediction scenarios is achieved by leveraging a conditional domain adversarial network, aligning DTI representations under diverse distributions. Experimental results within in-domain and cross-domain scenarios demonstrate that CAT-DTI model overall improves DTI prediction performance compared with previous methods.

Identification and Biological Evaluation of a Novel Small-Molecule Inhibitor of Ricin Toxin.

The plant-derived toxin ricin is classified as a type 2 ribosome-inactivating protein (RIP) and currently lacks effective clinical antidotes. The toxicity of ricin is mainly due to its ricin toxin A chain (RTA), which has become an important target for drug development. Previous studies have identified two essential binding pockets in the active site of RTA, but most existing inhibitors only target one of these pockets. In this study, we used computer-aided virtual screening to identify a compound called RSMI-29, which potentially interacts with both active pockets of RTA. We found that RSMI-29 can directly bind to RTA and effectively attenuate protein synthesis inhibition and rRNA depurination induced by RTA or ricin, thereby inhibiting their cytotoxic effects on cells in vitro. Moreover, RSMI-29 significantly reduced ricin-mediated damage to the liver, spleen, intestine, and lungs in mice, demonstrating its detoxification effect against ricin in vivo. RSMI-29 also exhibited excellent drug-like properties, featuring a typical structural moiety of known sulfonamides and barbiturates. These findings suggest that RSMI-29 is a novel small-molecule inhibitor that specifically targets ricin toxin A chain, providing a potential therapeutic option for ricin intoxication.

Targeting Moonlighting Enzymes in Cancer.

Moonlighting enzymes are multifunctional proteins that perform multiple functions beyond their primary role as catalytic enzymes. Extensive research and clinical practice have demonstrated their pivotal roles in the development and progression of cancer, making them promising targets for drug development. This article delves into multiple notable moonlighting enzymes, including GSK-3, GAPDH, and ENO1, and with a particular emphasis on an enigmatic phosphatase, PTP4A3. We scrutinize their distinct roles in cancer and the mechanisms that dictate their ability to switch roles. Lastly, we discuss the potential of an innovative approach to develop drugs targeting these moonlighting enzymes: target protein degradation. This strategy holds promise for effectively tackling moonlighting enzymes in the context of cancer therapy.

Treatment of highly virulent mammarenavirus infections-status quo and future directions.

INTRODUCTION: Mammarenaviruses are negative-sense bisegmented enveloped RNA viruses that are endemic in Africa, the Americas, and Europe. Several are highly virulent, causing acute human diseases associated with high case fatality rates, and are considered to be significant with respect to public health impact or bioterrorism threat. AREAS COVERED: This review summarizes the status quo of treatment development, starting with drugs that are in advanced stages of evaluation in early clinical trials, followed by promising candidate medical countermeasures emerging from bench analyses and investigational animal research. EXPERT OPINION: Specific therapeutic treatments for diseases caused by mammarenaviruses remain limited to the off-label use of ribavirin and transfusion of convalescent sera. Progress in identifying novel candidate medical countermeasures against mammarenavirus infection has been slow in part because of the biosafety and biosecurity requirements. However, novel methodologies and tools have enabled increasingly efficient high-throughput molecular screens of regulatory-agency-approved small-molecule drugs and led to the identification of several compounds that could be repurposed for the treatment of infection with several mammarenaviruses. Unfortunately, most of them have not yet been evaluated in vivo. The most promising treatment under development is a monoclonal antibody cocktail that is protective against multiple lineages of the Lassa virus in nonhuman primate disease models.

Potential Alzheimer's disease drug targets identified through microglial biology research.

INTRODUCTION: Microglia, the primary immune cells in the brain, play multifaceted roles in Alzheimer's disease (AD). Microglia can potentially mitigate the pathological progression of AD by clearing amyloid beta (Aß) deposits in the brain and through neurotrophic support. In contrast, disproportionate activation of microglial pro-inflammatory pathways, as well as excessive elimination of healthy synapses, can exacerbate neurodegeneration in AD. The challenge, therefore, lies in discerning the precise regulation of the contrasting microglial properties to harness their therapeutic potential in AD. AREAS COVERED: This review examines the evidence relevant to the disease-modifying effects of microglial manipulators in AD preclinical models. The deleterious pro-inflammatory effects of microglia in AD can be ameliorated via direct suppression or indirectly through metabolic manipulation, epigenetic targeting, and modulation of the gut-brain axis. Furthermore, microglial clearance of Aß deposits in AD can be enhanced via strategically targeting microglial membrane receptors, lysosomal functions, and metabolism. EXPERT OPINION: Given the intricate and diverse nature of microglial responses throughout the course of AD, therapeutic interventions directed at microglia warrant a tactical approach. This could entail employing therapeutic regimens, which concomitantly suppress pro-inflammatory microglial responses while selectively enhancing Aß phagocytosis.

Emerging therapies targeting growth factors in hepatocellular carcinoma.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a primary liver cancer that commonly arises in the background of chronic liver inflammation and/or cirrhosis. Chronic liver inflammation results in the production of different growth factors, remodeling of the microenvironment architecture into fibrosis, and eventually carcinogenesis. Overexpression of some growth factors has been associated with worse prognosis in patients with HCC. Targeted therapies against growth factors may disrupt cell signaling and the mechanisms that allow for cell survival (e.g. angiogenesis, proliferation, metastases). AREAS COVERED: We herein review potential growth factor targets of HCC and the limited research that exists regarding targeted therapy of these ligands and their receptors. We performed an extensive literature search to investigate preclinical studies, clinical research, and clinical trials. EXPERT OPINION: Systemic therapy for patients with HCC is continuing to evolve. Anti-angiogenic therapy holds the most promise among targeted therapy for growth factors among patients with HCC. Improving our understanding of growth factors in HCC will hopefully lead to the development of new targeted therapies and strategies for combination therapies with immune checkpoint inhibitors.

Advances in sarcopenia: mechanisms, therapeutic targets, and intervention strategies.

Sarcopenia is a multifactorial condition characterized by loss of muscle mass. It poses significant health risks in older adults worldwide. Both pharmacological and non-pharmacological approaches are reported to address this disease. Certain dietary patterns, such as adequate energy intake and essential amino acids, have shown positive outcomes in preserving muscle function. Various medications, including myostatin inhibitors, growth hormones, and activin type II receptor inhibitors, have been evaluated for their effectiveness in managing sarcopenia. However, it is important to consider the variable efficacy and potential side effects associated with these treatments. There are currently no drugs approved by the Food and Drug Administration for sarcopenia. The ongoing research aims to develop more effective strategies in the future. Our review of research on disease mechanisms and drug development will be a valuable contribution to future research endeavors.

The Promise of Therapeutic Psilocybin: An Evaluation of the 134 Clinical Trials, 54 Potential Indications, and 0 Marketing Approvals on ClinicalTrials.gov.

Introduction: Psilocybin, a tryptamine psychedelic, has been touted in the media both historically and recently as a potential game-changing mental health therapeutic. ClinicalTrials.gov has over one hundred and thirty psilocybin clinical trials listed covering the last twenty years. The single most important aspect of any therapeutic is to gain approval for marketing and thus enter the real-world phase of development. A typical new chemical entity progresses from inception to US Food and Drug Administration (FDA) approval in approximately 12 years and seeks approval for a single indication. Methods: An observational study was conducted with the available information on the ClinicalTrials.gov site to observe the extent of progress made demonstrating the clinical utility of psilocybin. Results: The results showed 134 psilocybin trials typically unblinded studies of 10-20 participants, recruited over years at a single site. Additionally, there have been only three advanced trials (1 Phase 2/3 and 2 Phase 3) submitted, and only in the last two years. Discussion: The hundreds of psilocybin clinical trials initiated over the past twenty years comprising a myriad of potential indications may actually be slowing this potential game-changing mental health therapeutic agent's approval and is costing excessive amounts of capital. To fully evaluate the actual potential of psilocybin, purposeful clinical trials need to be designed well, executed efficiently, and analyzed utilizing sequential and statistically valid processes for each potential indication. This will require a change from the current exploratory forays to defined, well-funded, sequential pharmaceutical development practices, including adequate and appropriate blinding of studies, statistical design to determine the number of participants and more importantly, professional expertise in conducting multicenter trials. Unfortunately, these results demonstrate little real progress towards FDA approval of psilocybin and a field with no clear direction forward.

Discovery of a novel and highly selective JAK3 inhibitor as a potent hair growth promoter.

JAK-STAT signalling pathway inhibitors have emerged as promising therapeutic agents for the treatment of hair loss. Among different JAK isoforms, JAK3 has become an ideal target for drug discovery because it only regulates a narrow spectrum of γc cytokines. Here, we report the discovery of MJ04, a novel and highly selective 3-pyrimidinylazaindole based JAK3 inhibitor, as a potential hair growth promoter with an IC50 of 2.03 nM. During in vivo efficacy assays, topical application of MJ04 on DHT-challenged AGA and athymic nude mice resulted in early onset of hair regrowth. Furthermore, MJ04 significantly promoted the growth of human hair follicles under ex-vivo conditions. MJ04 exhibited a reasonably good pharmacokinetic profile and demonstrated a favourable safety profile under in vivo and in vitro conditions. Taken together, we report MJ04 as a highly potent and selective JAK3 inhibitor that exhibits overall properties suitable for topical drug development and advancement to human clinical trials.

The preclinical discovery and clinical evaluation of tirzepatide for the treatment of type 2 diabetes.

INTRODUCTION: Despite numerous antidiabetic medications available for the treatment of type 2 diabetes, a substantial percentage of patients fail to achieve optimal glycemic control. Furthermore, the escalating obesity pandemic underscores the urgent need for effective relevant pharmacotherapies. Tirzepatide, a novel dual GIP and GLP-1 receptor agonist, offers a promising therapeutic option. AREAS COVERED: This review describes the discovery and clinical development of tirzepatide. Based on data from pivotal in vivo and in vitro studies, the authors present the pharmacodynamic profile of tirzepatide. Furthermore, they summarize data from the clinical trial programs that assessed the efficacy and safety of tirzepatide for the treatment of type 2 diabetes or obesity in a broad spectrum of patients, and discuss its therapeutic potential. EXPERT OPINION: Tirzepatide effectively reduces glucose levels and body weight in patients with type 2 diabetes and/or obesity, with a generally safe profile. Based on data from phase 3 clinical trials, several agencies have approved its use for the treatment of type 2 diabetes and obesity. Clinicians should be aware of possible adverse events, mainly mild-to-moderate gastrointestinal side effects. Overall, tirzepatide represents a promising treatment option for the treatment of type 2 diabetes.

From molecules to visuals: Empowering drug discovery and development with mass spectrometry imaging.

Over the past three decades, mass spectrometry imaging (MSI) has emerged as a valuable tool for the spatial localization of drugs and metabolites directly from tissue surfaces without the need for labels. MSI offers molecular specificity, making it increasingly popular in the pharmaceutical industry compared to conventional imaging techniques like quantitative whole-body autoradiography (QWBA) and immunohistochemistry, which are unable to distinguish parent drugs from metabolites. Across the industry, there has been a consistent uptake in the utilization of MSI to investigate drug and metabolite distribution patterns, and the integration of MSI with omics technologies in preclinical investigations. To continue the further adoption of MSI in drug discovery and development, we believe there are two key areas that need to be addressed. First, there is a need for accurate quantification of analytes from MSI distribution studies. Second, there is a need for increased interactions with regulatory agencies for guidance on the utility and incorporation of MSI techniques in regulatory filings. Ongoing efforts are being made to address these areas, and it is hoped that MSI will gain broader utilization within the industry, thereby becoming a critical ingredient in driving drug discovery and development.

[The revolution of AI in drug development]. / L'intelligence artificielle, une révolution dans le développement des médicaments.

Artificial intelligence and machine learning enable the construction of predictive models, which are currently used to assist in decision-making throughout the process of drug discovery and development. These computational models can be used to represent the heterogeneity of a disease, identify therapeutic targets, design and optimize drug candidates, and evaluate the efficacy of these drugs on virtual patients or digital twins. By combining detailed patient characteristics with the prediction of potential drug-candidate properties, artificial intelligence promotes the emergence of a "computational" precision medicine, allowing for more personalized treatments, better tailored to patient specificities with the aid of such predictive models. Based on such new capabilities, a mixed reality approach to the development of new drugs is being adopted by the pharmaceutical industry, which integrates the outputs of predictive virtual models with real-world empirical studies.

Title: L'intelligence artificielle, une révolution dans le développement des médicaments. Abstract: L'intelligence artificielle (IA) et l'apprentissage automatique produisent des modèles prédictifs qui aident à la prise de décisions dans le processus de découverte de nouveaux médicaments. Cette modélisation par ordinateur permet de représenter l'hétérogénéité d'une maladie, d'identifier des cibles thérapeutiques, de concevoir et optimiser des candidats-médicaments et d'évaluer ces médicaments sur des patients virtuels, ou des jumeaux numériques. En facilitant à la fois une connaissance détaillée des caractéristiques des patients et en prédisant les propriétés de multiples médicaments possibles, l'IA permet l'émergence d'une médecine de précision « computationnelle ¼ offrant des traitements parfaitement adaptés aux spécificités des patients.

Enhancing drug development and clinical studies with patient-centric sampling using microsampling techniques: Opportunities, challenges, and insights into liquid chromatography-mass spectrometry strategies.

Microsampling has revolutionized pharmaceutical drug development and clinical research by reducing sample volume requirements, allowing sample collection at home or nontraditional sites, minimizing animal and patient burden, and enabling more flexible study designs. This perspective paper discusses the transformative impact of microsampling and patient-centric sampling (PCS) techniques, emphasizing their advantages in drug development and clinical trials. We highlight the integration of liquid chromatography-mass spectrometry (LC-MS) strategies for analyzing PCS samples, focusing on our research experience and a review of current literatures. The paper reviews commercially available PCS devices, their regulatory status, and their application in clinical trials, underscoring the benefits of PCS in expanding patient enrollment diversity and improving study designs. We also address the operational challenges of implementing PCS, including the need for bridging studies to ensure data comparability between traditional and microsampling methods, and the analytical challenges posed by PCS samples. The paper proposes future directions for PCS, including the development of global regulatory standards, technological advancements to enhance user experience, the increased concern of sustainability and patient data privacy, and the integration of PCS with other technologies for improved performance in drug development and clinical studies. By advancing microsampling and PCS techniques, we aim to foster patient-centric approaches in pharmaceutical sciences, ultimately enhancing patient care and treatment efficacy.

Leveraging Modeling and Simulation to Enhance the Efficiency of Bioequivalence Approaches for Generic Drugs: Highlights from the 2023 Generic Drug Science and Research Initiatives Public Workshop.

The 2023 Generic Drug Science and Research Initiative Public Workshop organized by the U.S. Food and Drug Administration (FDA) discussed the research needs to improve and enhance bioequivalence (BE) approaches for generic drug development. FDA takes such research needs and panel discussions into account to develop its Generic Drug User Fee Amendments III (GDUFA III) Science and Research Initiatives specific to generics. During the five workshop sessions, presentations and panel discussions focused on identifying and addressing scientific gaps and research needs related to nitrosamine impurity issues, BE assessment for oral products, innovative BE approaches for long-acting injectable products, alternative BE approaches for orally inhaled products, and advanced BE methods for topical products. Specifically, this report highlights the discussions on how to improve BE assessment for developing generic drug products based on research priorities for leveraging quantitative methods and modeling, as well as artificial intelligence/machine learning (AI/ML).