Medicines

Drug repurposing is the process of discovering new therapeutic indications for already existing drugs. By using already approved molecules with known safety profiles, this approach reduces the time, costs, and failure rates associated with traditional drug development, accelerating the availability of new treatments to patients. Artificial Intelligence (AI) plays a crucial role in drug repurposing by exploiting various computational techniques to analyze and process big datasets of biological and medical information, predict similarities between biomolecules, and identify disease mechanisms. The purpose of this review is to explore the role of AI tools in drug repurposing and underline their applications across various medical domains, mainly in oncology, neurodegenerative disorders, and rare diseases. However, several challenges remain to be addressed. These include the need for a deeper understanding of molecular mechanisms, ethical concerns, regulatory requirements, and issues related to data quality and interpretability. Overall, AI-driven drug repurposing is an innovative and promising field that can transform medical research and drug development, covering unmet medical needs efficiently and cost-effectively.

Objectives: This study aims to assess differences in analgesia prescribing in UK primary care between individuals with osteoarthritis who have a recorded exposure to cannabis use and those who do not. Methods: This population-based retrospective cohort study included opioid-naïve patients with osteoarthritis (aged 25–85 years) who were active in Clinical Practice Research Datalink Aurum between 1 January 1995 and 15 December 2023. Patients with osteoarthritis who had current or historic cannabis use recorded were matched to two unexposed individuals by age, sex, smoking status, and health authority. Patients were followed up to assess prescriptions of analgesia. Cox regression was performed adjusted for age, sex, and ethnicity. Results: 662 exposed patients were matched to 1319 unexposed patients. Cannabis-exposed individuals were more likely to be prescribed opioids (adjusted hazard ratio (HR): 2.06; 95% confidence interval (CI): 1.74–2.43; p < 0.001), gabapentinoids (HR: 3.31; 95% CI: 2.34–4.67; p < 0.001), non-steroidal anti-inflammatory drugs (HR: 1.99; 95% CI: 1.72–2.31; p < 0.001), tricyclic antidepressants (HR: 2.64; 95% CI: 2.03–3.44; p < 0.001), other antidepressants (HR: 7.22; 95% CI: 5.24–9.94; p < 0.001), and paracetamol (HR: 3.30; 95% CI: 2.43–4.48; p < 0.001). Conclusions: This study suggests there is an association between coded exposure to cannabis in UK primary care records and increased prescribing of analgesia. Given the relative scarcity of recorded cannabis use relative to its prevalence in the general population, these findings must be interpreted cautiously. The increased hazard of using analgesia and mortality within the cannabis-exposed cohort may be confounded by socioeconomic status and a higher likelihood of coding cannabis use in those experiencing adverse effects after consumption or cannabis misuse disorder.

Background/Objectives: Dilated cardiomyopathy (DCM) is a prevalent and life-threatening heart muscle disease often caused by titin (TTN) truncating variants (TTNtv). While TTNtvs are the most common genetic cause of heritable DCM, the precise downstream regulatory mechanisms linking TTN deficiency to cardiac dysfunction and maladaptive fibrotic remodeling remain incompletely understood. This study aimed to identify key epigenetic regulators of TTN-mediated gene expression and explore their potential as therapeutic targets, utilizing human patient data and in vitro models. Methods: We analyzed RNA sequencing (RNA-seq) data from left ventricles of non-failing donors and cardiomyopathy patients (DCM, HCM, PPCM) (GSE141910). To model TTN deficiency, we silenced TTN in human iPSC-derived cardiomyocytes (iPSC-CMs) and evaluated changes in cardiac function genes (MYH6, NPPA) and fibrosis-associated genes (COL1A1, COL3A1, COL14A1). We further tested the effects of TMP-195, a class IIa histone deacetylase (HDAC) inhibitor, and individual knockdowns of HDAC4/5/7/9. Results: In both human patient data and the TTN knockdown iPSC-CM model, TTN deficiency suppressed MYH6 and NPPA while upregulating fibrosis-associated genes. Treatment with TMP-195 restored NPPA and MYH6 expression and suppressed collagen genes, without altering TTN expression. Among the HDACs tested, HDAC5 knockdown was most consistently associated with improved cardiac markers and reduced fibrotic gene expression. Co-silencing TTN and HDAC5 replicated these beneficial effects. Furthermore, the administration of TMP-195 enhanced the modulation of NPPA and COL1A1, though its impact on COL3A1 and COL14A1 was not similarly enhanced. Conclusions: Our findings identify HDAC5 as a key epigenetic regulator of maladaptive gene expression in TTN deficiency. Although the precise mechanisms remain to be clarified, the ability of pharmacological HDAC5 inhibition with TMP-195 to reverse TTN-deficiency-induced gene dysregulation highlights its promising translational potential for TTN-related cardiomyopathies.