Drug Development Research Articles

Background: Current preclinical murine models for heart failure with preserved ejection fraction (HFpEF) require prolonged modeling periods, pose significant challenges to fast screening in drug development. In response, our study sought to develop a novel, shortened, multifactorial HFpEF mouse model that coupled obesity, hyperglycemia, hypertension and cardiac hypertrophy to closely mirrors the cardio-metabolic phenotypes observed in human patients. Methods: Diet-induced obesity (DIO) male mice were administered with angiotensin II (Ang II) for 4 weeks via osmotic mini pumps. LCZ696 (60mpk), a novel FDA-approved medicine in heart failure patients, was administrated (P.O., QD) one day after angiotensin II infusion for 4 weeks. Results: The adult (27 week-old) DIO male mice developed overt overweight and hyperglycemia. After 4-weeks infusion by Ang II, DIO mice were conducted with echocardiography to identify the left ventricle structural and functional alterations. Typical phenotypes as observed in human HFpEF patients, were detected in Ang II-induced DIO mice, for example, unchanged LVEF, elevated IVRT and increased heart weight and LVPWTs/d, indicating that the diastolic dysfunction and cardiac hypertrophy happened in the model mice. Post-life analysis, heart tissue collection and histopathalogical stainings revealed an increased level of cardiac fibrosis with infiltration of inflammatory cells. Blood chemistry analysis also revealed an upregulation in cardiac biomarker NT-proBNP and inflammatory biomarker IL-6. Administration of LCZ696 significantly attenuated the cardiometabolic abnormalities with restored diastolic function, reduced cardiac hypertrophy and myocardial fibrosis. Conclusion: We have successfully developed a rapid mouse model that closely mimics human HFpEF, with modeling time around 4 weeks and a robust validation using LCZ696, offering a fast, valuable new platform for advancing therapeutic development of HFpEF treatment.

Generative Artificial Intelligence (AI) frameworks, such as Variational Autoencoders (VAEs), have proven powerful in learning structured representations from complex, high-dimensional data. In pharmacometrics (PMX), nonlinear mixed effects (NLME) modeling is widely used to capture inter-individual variability and link covariates to characterize parameters with the goal of informing key decisions in drug research and development. This research combines the strengths of both approaches by introducing a VAE framework specifically designed for NLME modeling. The proposed method integrates the flexibility of generative AI with the interpretability and robustness of mechanism-based PMX modeling. To advance covariate selection in PMX, we replace the Evidence Lower Bound objective in VAEs with an objective function based on the corrected Bayesian information criterion. This enables the simultaneous evaluation of all potential covariate-parameter combinations, thereby allowing for automated and joint estimation of population parameters and covariate selection within a single run. Manual selection and repeated model fitting across covariate combinations are no longer required. We demonstrate the effectiveness of this combined AI-PMX approach with two representative cases. As the first generative AI-based optimization method for NLME modeling, the VAE achieves high-quality results in a single run, outperforming traditional stepwise procedures in terms of efficiency. As such, the presented approach facilitates automated model development, advancing PMX and its applications in model-informed drug development.

Background: In drug development, rodent models that faithfully recapitulate human disease are critical for evaluating the therapeutic effects and confirming the mechanisms of action of novel targets. For heart failure with preserved ejection fraction (HFpEF), ZSF1 obese rats and high-fat diet (HFD)+L-NAME-treated C57BL/6N mice are two widely-used preclinical rodent models. Both exhibit impaired diastolic function with normal ejection fraction, but the HFpEF phenotype in HFD+L–NAME mice tends to be relatively mild. While E/e' is clinically established as a surrogate for LV filling pressure, there is limited assessment of LV filling pressure surrogates including E/e' in rodent models. Hypothesis: Modifying treatment protocol promotes the development of a more robust HFpEF phenotype in rodent models. Furthermore, employing a combination of multiple readouts enhances the prediction of disease status in these preclinical models. Methods: We increased L-NAME dose and increased duration of HFD+L-NAME model induction to 20-40 weeks in male 12 week old C57BL/6N mice. In female ZSF1 obese rats, we performed longitudinal assessment from 16-40 weeks of age. Multiple readouts were collected in HFD+L–NAME mice alongside age-matched healthy controls, as well as female ZSF1 obese rats with ZSF1 lean controls to confirm their HFpEF phenotype and comorbidities including echocardiography (conventional, LV and LA strain analysis, LV HDF using Vevo Strain 2.0), treadmill testing, organ masses, and invasive hemodynamics (Millar PV catheter). Results: Increasing the dose of L-NAME in drinking water to 1g/L and the treatment period of both HFD and L-NAME to >20 weeks enhanced HFpEF phenotype characterized by obesity, hypertension, LV hypertrophy, elevated E/e’ and LVEDP, impaired LV strain and HDF, impaired LA strain, and reduced exercise capacity. Similarly, female ZSF1 obese rats developed a robust HFpEF phenotype marked by obesity, hypertension, LV hypertrophy, elevated E/e’ and LVEDP, impaired LA strain, and reduced exercise capacity. Using linear regression, we identified echocardiographic predictors of elevated LVEDP in both models that outperform E/e’ including LV HDF strength, LA reservoir strain, LVMI, and IVRT. Conclusions: Increased L-NAME dose and prolonged model induction with HFD+L-NAME produce a robust HFpEF phenotype. Additionally, strain analysis is a more reliable predictor of elevated LV filling pressure than E/e’ in HFpEF preclinical rodent models.

Costunolide (COS) is a bioactive sesquiterpene lactone compound extracted from Aucklandia lappa, known for its anticancer, anti-inflammatory, and antioxidant properties, aligning with the traditional Chinese medicine theory of "clearing heat and dispersing nodules" in the treatment of breast ailments. Network pharmacology identified EGFR as the core target of COS, with enrichment analysis revealing the EGFR/ERK/AKT axis as a key pathway. Molecular docking demonstrated strong binding affinity of COS to the EGFR kinase domain, relying on hydrogen bonds and hydrophobic interactions. In vitro experiments showed that COS inhibited TNBC cell proliferation and induced apoptosis. Mechanistically, COS increased EGFR ubiquitination, leading to a decrease in EGFR protein levels, thereby inhibiting EGFR phosphorylation and the activation of downstream ERK and Akt signaling pathways. EGF could partially reverse the growth inhibitory effects of COS, confirming the critical role of EGFR. This study elucidates that COS exerts its anti-TNBC effects by inducing EGFR ubiquitination and degradation, thereby inhibiting the ERK/AKT signaling pathway. This finding integrates traditional Chinese medicine theory with modern molecular oncology mechanisms, providing a reference for the development of plant-derived multi-target anticancer drugs.

Chagas disease affects around 6-8 million people worldwide. The available treatments have considerable limitations, including their uncertain efficacy in the chronic phase of the disease in adults, their unfavorable safety profile that usually compromises adherence to treatment, their long duration, and the emergence of resistant strains. All these considerations justify the continuous search for improved therapies.Informatics has been increasingly integrated into all levels of biomedical sciences, including the discovery and development of new drugs. In silico methods are relevant in all domains of therapeutics, but especially in the field of neglected diseases, in which their adoption can leverage the active participation of low- and middle-income countries (the ones historically affected by these diseases) in the development of new diagnostic and therapeutic options.This chapter describes the in silico methodologies that can be used to validate new pharmacological targets, compile data sets to train and/or validate computational models to apply in in silico screening campaigns, and implement retrospective and prospective in silico screening experiments.

The 3-aryl-imidazo[1,2-a]pyridines are among the most promising molecular frameworks in drug discovery and development; however, their sulfonyl analogues remain largely underexplored. In this study, we report a base-mediated annulative-sulfonylation of 4-(pseudo)halo-2-aminopyridines using (E)-β-iodovinyl sulfones in polyethylene glycol (PEG400), resulting in the formation of 7-sulfonyl-derived imidazo[1,2-a]pyridines in good to high yields. Remarkably, the 4-(pseudo)halo-2-aminopyridines allow unexpected sulfonyl migration, leading to the first preparative synthesis of imidazo[1,2-a]pyridine-derived sulfone analogues. Conversely, other substituted 2-aminopyridines participate in a desulfonylative-annulation using (E)-β-iodovinyl sulfones to afford 3-substituted-imidazo[1,2-a]pyridines in moderate to high yields. Importantly, this metal-free protocol is versatile, accommodating a wide range of substrates while demonstrating good functional group tolerance and compatibility. Notably, the method has proven effective in synthesizing 3,7-diphenyl-imidazo[1,2-a]pyridine, a tyrosine kinase (KDR) inhibitor, as well as its isomeric analogue. Furthermore, gram-scale reactions have been successfully conducted, and potential mechanistic pathways have been rationalized based on existing experimental results.

Background: The cardiac hormone atrial natriuretic peptide is the endogenous ligand for the guanylyl cyclase A (GC-A) receptor. The ANP/GC-A/cGMP pathway is a key regulator of cardiorenal and metabolic homeostasis. Beyond its classical natriuretic and vasodilatory roles, emerging evidence reveals that ANP via GC-A stimulates lipolysis in human adipocytes and modulates insulin secretion. Notably, the ANP gene variant rs5068, which enhances ANP production, is associated with reduced risk of obesity and metabolic syndrome in humans. We recently engineered CRRL191, a novel best-in-class GC-A agonist, with superior receptor activation and greater resistance to degradation by neprilysin and insulin degrading enzyme resulting in greater blood pressure lowering and natriuretic effects than ANP. Given the metabolic properties of GC-A signaling, we investigated CRRL191’s metabolic effects on lipolysis and insulin secretion in pancreatic, including its interaction with GLP-1. Hypothesis: CRRL191 exerts potent lipolytic and insulinotropic effects and synergizes with GLP-1 to enhance insulin secretion. Methods: Human visceral adipocytes were treated with CRRL191 (10 -8 -10 -6 M) for 6 hrs. Lipolysis was assessed by measuring glycerol and non-esterified fatty acids (NEFA) in supernatants. Rat pancreatic beta cells (INS-1) were stimulated treated with CRRL191 (10 -10 -10 -6 M), GLP-1 (10 -10 -10 -6 M) alone or their combination for 1 hr. Insulin secretion was quantified by ELISA. Results: CRRL191 stimulated lipolysis in human visceral adipocytes (10 -8 -10 -6 M), increasing glycerol and NEFA release. CRRL191 induced greater glycerol release than GLP-1 across all tested doses, with low dose CRRL191 (10 -10 M) notably enhancing NEFA production. In INS-1 cells, CRRL191 dose dependently increased insulin secretion under hyperglycemic conditions, demonstrating superior potency at lower concentrations (10 -10 and 10 -8 M) compared to GLP-1. Remarkably, co-administration of CRRL191 with GLP-1 amplified insulin release beyond levels achieved by either peptide alone. Conclusion: CRRL191 is a potent GC-A agonist that robustly stimulates lipolysis in visceral adipocytes and enhances insulin secretion in pancreatic beta cells. Its synergistic interaction with GLP-1 highlights a novel therapeutic avenue targeting the GC-A/cGMP pathway for integrated treatment of cardiometabolic diseases. These findings support further evaluation of CRRL191 as a promising candidate for cardiometabolic drug development.

Amastigotes are the replicative intracellular life cycle stage of the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas disease. They have the ability to proliferate in any nucleated mammalian cell. A greater understanding of amastigote biology would greatly aid drug development since this life cycle stage is the principal target of chemotherapy. Reports have linked recrudescence following drug treatment with the possible existence of a quiescent amastigote phenotype. However, the lack of a rapid and straightforward method for isolating amastigotes from infected host cells has limited research progress in this area. This is particularly the case with omics technology, where the current complex fractionation and purification procedures can act to perturb RNA and protein expression. Here, we outline a methodology that largely overcomes these problems. Our protocol exploits MP Bio-Lysing Matrix M tubes to promote the differential lysis of host cells and the release of intact amastigotes in a 1-min time frame. Immediate treatment of the lysate with CellCover reagent then maintains RNA and protein in their native states. Amastigotes stabilized in this way can undergo further manipulations, such as cell sorting, without modification of their proteome or transcriptome profiles. This methodology, which is flexible and widely applicable, should greatly benefit research into the intracellular life cycle of T. cruzi.

Background: Early adoption of PCSK9 monoclonal antibodies and small-interfering RNA therapies depends on clinical-trial access. Yet communities with the highest cardiovascular burden—often socioeconomically deprived—are under-represented in lipid-lowering trials. Hypothesis: In the Southern U.S, Phase III lipid-lowering trial sites cluster near socioeconomically advantaged cities, forcing residents of more deprived cities to travel farther to participate. Aim: Quantify association between city-level socioeconomic deprivation and drive time to the nearest Phase III trial site. Methods: We conducted a cross-sectional geospatial analysis of Phase III trials for Inclisiran, Evolocumab, and Alirocumab initiated between 2015-2020. Trial locations were extracted from ClinicalTrials.gov, geocoded, and de-duplicated. All Census-defined Southern U.S cities with ≥50,000 residents in 2020 were included (n=284). Socioeconomic deprivation was measured with the Area Deprivation Index (ADI; higher=greater deprivation). Typical drive time from each city center to nearest trial site was computed using Google Distance Matrix API. Minority-majority status (≥50% racial minority) served as a covariate. Generalized Estimating Equations with a gamma distribution and log link, clustered by city, estimated percent change in drive time per one-point ADI increment. Results: Of the 284 cities in the study, 151 (53%) were minority-majority. 73 cities (26%) contained a trial site and yielded 849 city–site dyads. Median drive time was 36 min (IQR 21–91); 58% of cities required ≥30 min and 38% ≥60 min of travel. Each one-point ADI increase was associated with a 2.1% longer drive time (β=0.0212, 95% CI 0.017–0.025; p<0.001). Moving from the 25th to the 75th ADI percentile more than doubled predicted travel burden. After adjustment, minority-majority cities had a 21.7% shorter drive time than non-minority-majority cities (β = -0.245, 95% CI -0.438 to -0.053; p=0.013), reflecting concentration of sites in a few large, diverse hubs. Results were robust to driving distance, PCSK9 inhibitor-only analyses, and city-level clustering. Conclusions: Southern U.S cities with greater socioeconomic deprivation face substantially longer travel times to Phase III lipid-lowering clinical trials, potentially limiting early therapeutic access and perpetuating evidence gaps. Strategic placement of future trial sites in deprived areas is essential for equity and generalizability in cardiovascular drug development.

Background: Platelets express 12-lipoxygenase (ALOX12) and 12/15-lipoxygenase (ALOX15) which exhibit positional specificity in the oxygenation of polyunsaturated fatty acids such as arachidonic acid. Although ALOX12 has been studied extensively in platelets, its role in platelet function is controversial. On the other hand, the role of ALOX15 in platelet activation has never been investigated. Hypothesis: Does ALOX15 (aka 12/15-LOX) play a role in platelet activation and hemostasis? Methods: 12/15-LOX -/- mice as well as pharmacological and molecular approaches were used. Results: Genetic deletion of 12/15-LOX suppressed thrombin-induced PAR4 myristoylation and its membrane trafficking causing a reduction in its interaction with PAR3 in mouse platelets. We also found that 12/15-LOX via activation of protein kinase Cq (PKCq) mediates N-myristoyltransferase 1 (NMT1) phosphorylation in the modulation of thrombin-induced PAR4 myristoylation. In line with these observations, genetic deletion or inhibition of 12/15-LOX or pharmacological blockade of PKCq or NMT1 attenuated thrombin-induced PAR4 myristoylation, trafficking, and its interaction with PAR3 leading to reduced mouse platelet activation. Consistent with these observations, genetic deletion or inhibition of 12/15-LOX or blockade of PKCq or NMT1 exhibited prolonged bleeding time and delayed clotting and clot-retraction times in mice. Intriguingly, thrombin induces myristoylation and trafficking of both PAR1 and PAR4 facilitating their interaction in the plasma membrane of human platelets and inhibition of 15-LOX1, the human orthologue of murine 12/15-LOX, attenuated these effects. In addition, inhibition of 15-LOX1 blunted thrombin-induced human platelet activation and clot-retraction. Thus, our findings unfold a novel role for 12/15-LOX in the myristoylation and trafficking of PAR4 in mice and PAR1/4 in humans facilitating PAR3/4 interactions in mice and PAR1/4 interactions in humans leading to platelet activation and hemostasis. Conclusions: Our observations reveal a novel role for 12/15-LOX in the myristoylation and trafficking of PARs leading to their interactions in the plasma membrane potentiating platelet activation and hemostasis. Based on these observations, 12/15-LOX could be an ideal target for drug development against platelet disorders.

Background: Cardiac gene therapy holds the potential to transform the treatment of inherited and acquired cardiovascular diseases by correcting the causative basis of disease. However, despite extensive research, progress has been hindered, primarily due to the limited translation of pre-clinical models to human clinical settings. More advanced, human-based pre-clinical platforms are urgently needed to bridge the gap from bench to bedside. Human living myocardial slices (LMS), are 3D tissue sections with native multicellularity, structure and function, providing a promising platform to address these challenges. Aims: Our study aimed to develop a platform for viral transduction of cardiomyocytes in human LMS, to advance pre-clinical gene therapy research and accelerate cardiac nucleic acid drug development. Methods: LMS prepared from failing and non-failing donor hearts were cultured at physiological preload in a specialized biomimetic culture chamber with continuous force monitoring. After 2-4 days in culture, adenovirus carrying a fluorescent probe (GFP or mCherry) with either a ubiquitous or a cardiac-specific promoter was applied directly to the LMS surface at varying multiplicities of infection (MOIs). Slice contractility was monitored throughout culture to assess virus and transgene effects on function. At culture endpoint (5-10 days post transduction), slices were characterized using isometric Frank-Starling experiments in a custom bioreactor, fixed and probed for protein expression with antibodies, visualized via confocal microscopy, and lysed for transgene protein expression analysis via western blotting. Results: We demonstrate reproducible adenoviral transduction of GFP and mCherry in both cardiomyocytes and non-cardiomyocytes without compromising contractile function. An MOI-dependent increase in transduction and protein expression was observed, confirmed through confocal imaging (Figure 1) and western blot analysis (Figure 2). Conclusion: This proof-of-concept study establishes feasibility of viral transduction of human LMS from explanted hearts, opening new avenues for translational heart research in the gene therapy space. Our expertise in LMS methodology positions us to develop this platform as a novel pre-clinical tool for genetic therapies, with future studies focusing on transducing failing human hearts with cardiac recovery-associated proteins.

Introduction: Aortic aneurysms (AAs), including thoracic (TAA) and abdominal (AAA) types, are associated with a high risk of dissection and rupture, with no pharmacological therapies are available to slow or prevent progression. Multi-omics strategies offer promise for discovering therapeutic targets. While prior studies based on genomic and transcriptomic data have identified lipoprotein(a) and PCSK9 as potential targets, proteomic and metabolomic analyses remain limited. Methods: We employed two-sample Mendelian randomization (MR), summary-data-based MR (SMR) with false discovery rate correction, and Bayesian colocalization analysis with HEIDI testing to evaluate the association between plasma proteins and AA. Proteins significant in two out of three analyses were considered potential drug targets, while those significant in all three were defined as core therapeutic targets. Potential side effects of core targets were evaluated using phenome-wide association studies (PheWAS). Additional MR analyses identified AA-related metabolites, and mediation analysis via the delta method was used to assess causal pathways linking proteins and metabolites. Results: We identified five proteins as potential therapeutic targets: LTBP4 (positive association with AA, TAA), IL6R (negative association with AA, AAA), SMPD1 and ACAT2 (positive association with AA), and PCSK9 (positive association with AAA). SMPD1 emerged as a core therapeutic target for AAA, with significant associations in MR (OR = 1.39, 95% CI: 1.21–1.60, P = 2.04E-6), SMR (OR = 1.42, 95% CI: 1.21–1.67, P = 1.94E-5), and colocalization (PPH4 = 98.76%), and no adverse phenotypes detected in PheWAS. Metabolite MR further identified lignoceroyl sphingomyelin, N-palmitoyl-sphinganine, and N-palmitoyl-sphingosine as associated with AA; oleoyl-linoleoyl-glycerol, N-palmitoyl-sphinganine, and N-palmitoyl-sphingosine with AAA. Mediation analysis showed that N-palmitoyl-sphingosine significantly mediated the effect of SMPD1 on AA (effect proportion: 23.1%, 95% CI: 3.3%–93.6%) and AAA (34.4%, 95% CI: 2.7%–66.0%). Conclusion: This study identifies five plasma proteins and four metabolites as potential therapeutic targets for AA. To our knowledge, this is the first study to highlight SMPD1 as a core therapeutic target for AAA, likely acting through ceramide metabolism involving N-palmitoyl-sphingosine. These findings offer novel mechanistic insights into AAA and suggest promising directions for drug development.

Multiple myeloma is a plasma cell malignancy that is susceptible to drugs targeting protein homeostasis such as thalidomide analogues and proteasome inhibitors. Thalidomide analogues modulate the activity of DDB1/CUL4 E3-ligase complexes to perturb substrate recognition and proteasomal degradation thereof. We hypothesised that the cellular pool of DDB1/CUL4 associated factors (DCAFs) may mediate other essential plasma cell processes and offer new targets for therapeutic intervention. Unbiased genetic screening identified DCAF1 (also known as Vpr-binding protein; VPRBP) as essential for myeloma cell survival with a multidomain structure offering several distinct opportunities for drug development. Utilising B32B3, a previously disclosed DCAF1 kinase inhibitor as a template, we developed a series of analogues with enhanced anti-myeloma potency. As anti-myeloma activity did not associate with dephosphorylation of known DCAF1 kinase substrates, we correlated drug-induced cellular phenotypes with whole-genome CRISPR/Cas9 resistance screening to further define mechanistic activity. These studies identified B32B3 analogues as microtubular destabilising agents with potential DCAF1 kinase independent properties and in vivo efficacy in multiple myeloma and lymphoma.

Hypoxia is one of the common characteristics of solid tumors, primarily resulting from an imbalance between rapid tumor proliferation and disordered angiogenesis. Hypoxic heterogeneity promotes tumor invasion and metastasis, metabolic reprogramming, immune suppression, and angiogenesis. Moreover, tumor hypoxia is one of the major drivers of widespread drug resistance observed in cancer therapy. Hypoxia also presents opportunities for targeted tumor therapy with hypoxia-targeted prodrugs (HAPs) showing great potential in cancer treatment. This perspective summarizes the fundamental principles, major classifications, and drug design strategies of HAPs, as well as highlights the innovative integration of HAPs with other therapeutic modalities. This article endeavors to provide a comprehensive perspective on the evolving field of hypoxia-targeting agents, offering valuable insights into future drug development.

Background: Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with progressive atrial remodeling. Although clinical interventions often target the left atrium, molecular differences between atrial chambers may influence AF persistence and therapeutic response. Hypothesis: We hypothesized that transcriptomic signatures consistently differentiate the left atrial appendage (LAA) from the right atrial appendage (RAA) in patients with AF and that conserved biomarkers can be identified across independent datasets. Goals: To identify robust, cross-dataset gene expression markers distinguishing LAA from RAA, with potential implications for chamber-specific therapeutic targeting in AF. Methods: Gene expression profiles were obtained from three publicly available microarray datasets (GSE41177, GSE115574, and GSE79768), comprising 85 atrial tissue samples. Differentially expressed genes (DEGs) between LAA and RAA were identified using the limma package. Functional enrichment analysis was conducted using Gene Ontology and KEGG databases. Protein–protein interaction (PPI) networks were constructed using STRING to identify hub genes. Expression validation was visualized through boxplots. Results: We identified 140 unique DEGs, with 32 genes overlapping in two or more datasets. Enrichment analysis revealed significant involvement in atrial morphogenesis, cardiac chamber specification, and bone morphogenetic protein (BMP) signaling. PPI network analysis highlighted BMP10 and PITX2 as central hub genes, each exhibiting consistently enriched expression in LAA across datasets. These patterns were confirmed through cross-dataset boxplot visualization. Conclusion: BMP10 and PITX2 represent conserved transcriptomic markers differentiating LAA from RAA in patients with AF. These genes may serve as biomarkers of chamber-specific remodeling and inform personalized AF management strategies, including targeted ablation or atrial-selective drug development.

Introduction: Heart failure with preserved ejection fraction (HFpEF) affects over 32 million people globally, and has a 30% mortality within one year of first hospitalization. Currently there are no HFpEF medications that are disease modifying or reduce mortality. As genomic-led drug discovery has demonstrated a 2.6-fold improvement in successful drug development, there have been ‘urgent’ calls to understand the genetic architecture of HFpEF. Despite this, our understanding remains poor; the two dedicated genome-wide association studies (GWAS) discovered only two, marginally significant loci. The primary limitation is imprecise phenotyping in genetic biobanks. For example, the most common heart failure code in the UK Biobank (UKB) is “heart failure, unspecified”) Aim: To use machine learning to decipher the full genetic architecture of HFpEF. Methods: To uncover the full genetic architecture of HFpEF, we performed the following: a) Trained ML models to predict a precise HFpEF phenotype, b) Deployed models in UKB and assigned participants a HFpEF probability and c) Conducted GWAS on these predicted HFpEF probabilities. We trained 3 separate ML models to predict HFpEF: 1) Prediction from 40 biomarkers using XGBoost 2) Prediction from ECGs using neural networks, and 3) Prediction from Cardiac MRIs using neural networks. We deployed these 3 models on UKB participants which generated a HFpEF probability from which we conducted 3 GWAS. We then conducted proteomic analysis to identify proteins highly expressed in participants with high probability of HFpEF in UKB. Results: Our 3 ML models predicted HFpEF with acceptable accuracy (AUC for biomarker XGBoost model: 0.85 (95%CI: 0.84-0.86), AUC for ECG neural network: 0.79 (0.78-0.80), and AUC for cardiac MRI: 0.75 (0.74-0.76). Our genome-wide association studies reveal 47 novel loci for HFpEF, with leading loci including: FTO, PRKAG2, AL162414, ITGA4, CAPN8, and HABP4. Proteomic analysis revealing a mixture of known associated proteins (e.g. NT-proBNP, Renin, and Leptin) and novel proteins associated with HFpEF, such as: Fatty Acid Binding Protein 4, Synuclein Gamma, and Insulin-like Growth Factor Binding Protein 1. Conclusion: Machine learning facilitates the prediction of precise HFpEF phenotypes, which in turn reveals the full genetic architecture of HFpEF. Our genetic and proteomic data can serve as therapeutic targets for future research to create truly disease modifying HFpEF medications.

The pharmaceutical industry is transforming with the advent of Industry 5.0, which is marked by integrating artificial intelligence (AI) into drug discovery and development. AI technologies, such as machine learning, deep learning, and natural language processing, revolutionize the traditional drug development pipeline by accelerating the identification of novel drug candidates, optimizing clinical trial designs, and personalizing therapies. Moreover, AI models enhance the prediction of drug efficacy, toxicity, and patient responses, minimizing the risk of failure of clinical trials. Nevertheless, despite these advancements, challenges remain in integrating AI into the pharmaceutical workflow, including data quality, regulatory concerns, and the need for interdisciplinary collaboration. This review explores the current state of AI applications in drug discovery, drug formulation and optimization, pharmacokinetics and pharmacodynamics, drug manufacturing and quality control, regulatory compliance and pharmacovigilance. Overall, AI is poised to redefine the landscape of drug discovery and development, fostering a new era of precision medicine and transforming patient outcomes globally, especially in the era of Industry 5.0.

Animal venom, known for its complex biochemical composition, presents a valuable source of therapeutic molecules, particularly for antiviral applications. Despite this potential, the industrial use of venom remains limited, with fewer than a dozen venom-derived compounds reaching commercial markets. This study underscores the significance of exploring venom’s natural diversity as a reservoir for novel bioactive compounds that could drive innovative drug development. We investigated the venom of the Moroccan black scorpion Androctonus mauritanicus (Am) , applying solid-phase extraction (SPE) and high-performance reversed-phase liquid chromatography (RP-HPLC) to fractionate the venom into 80 distinct samples. These fractions were subjected to detailed analysis using advanced mass spectrometry techniques, including ESI-MS, Q-TOF LC/MS, and Q-Exactive LC/MS. In total, 507 unique molecular masses were identified, with several fractions enriched in neurotoxins targeting ion channels (NaScTxs, KScTxs, CaScTxs, and ClScTxs), highlighting their therapeutic relevance. Fractions containing inhibitory molecules targeting the receptor-binding domain (RBD) of the SARS-CoV-2 Spike S protein were identified through in vitro validation via competitive ELISA, showing multiple levels of inhibitory potential. These findings demonstrate the antiviral activity of venom-derived molecules and reveal promising opportunities for venom-based industrial applications targeting SARS-CoV-2. In conclusion, this study not only emphasises the antiviral properties of specific venom molecules but also opens pathways for industrial drug development, offering potential tools to combat emerging viral diseases.

The synthesis of amide building blocks is crucial for producing diverse amide-containing compounds such as peptides, proteins, and amino acids. The demand for innovative methods of amide bond derivatives, considered as vital nonclassical bioisosteres, is steadily increasing because of its pivotal role in drug development. A highly cost-effective and efficient approach for generating amide functional groups involves the metal-catalyzed hydration of nitriles, offering profound implications for both academic and industrial sectors. This review explores the recent successful catalytic systems, encompassing both homogeneous and heterogeneous solid catalysts that enhance the catalytic transformation of nitriles into amides. Furthermore, theoretical studies employing density functional theory calculations to elucidate the cooperative mechanism between the catalyst and the carbon-nitrogen bond in nitriles are overviewed.

The enantioselective construction of all-carbon quaternary stereogenic centers adjacent to N-heterocycles remains a long-standing challenge in asymmetric catalysis. Herein we report a copper-catalyzed enantioselective hydropyridylation of 1,1-disubstituted allenes with 2-halopyridines that proceeds via a nucleophilic aromatic substitution (SNAr) pathway. This transformation enables the efficient synthesis of α-quaternary N-heterocyclic compounds with a broad substrate scope in high yields (up to 96%) with excellent enantioselectivities (up to 99% ee). The methodology is compatible with various functional groups and N-heterocycles and can be extended to copper-catalyzed boropyridylation, affording versatile alkenylboronates. Mechanistic studies, including deuterium labeling, kinetic isotope effect analysis, and DFT calculations, support a 2,3-hydrocupration followed by a stereodetermining SNAr step. This strategy provides a practical and general approach for constructing structurally diverse azaarene-containing quaternary centers, which are potentially valuable for drug discovery and development.