Artificial intelligence (AI), coupled with machine learning (ML) has been rapidly incorporated into pharmaceutical discovery and development. We reviewed 53 publications from 2018-2026 to summarize current applications of AI/ML in drug discovery. AI and ML have potential to impact every step of the drug development pipeline and have already shown to drastically reduce time frames for developing therapeutics. Specific deep learning models such as graph neural networks and transformers have shown promise in de novo molecular generation, molecular property prediction, and target recognition. Accurate protein structure prediction using AlphaFold allows for exploration of drug-target binding. De novo drug design with reinforcement learning allows for targeted design of molecules with desired properties. Machine learning models for QSAR provide more accurate toxicity predictions and ADMET profiling to avoid potential failures during drug development. However, current limitations include lack of interpretability, data limitations, and lack of regulatory approval. According to a review of recent literature, AI has the potential to decrease the time required for drug discovery from years to months and lower the cost of drug development. This review discusses recent advances, successful clinical examples, and opportunities for artificial intelligence/machine learning in drug discovery.

Background: Stroke-like migraine attacks after radiation therapy (SMART) syndrome is a rare, delayed complication of cranial irradiation characterized by subacute, potentially reversible neurological deficits and distinctive imaging features. Its diagnosis is particularly challenging in patients with metastatic brain disease, where clinical and radiological findings overlap with tumor progression, radiation necrosis, and seizure-related phenomena. Case Presentation: We report the case of a 43-year-old male with stage IV ALK-positive non-small-cell lung adenocarcinoma with extensive brain metastases who developed acute global aphasia and altered mental status following multiple courses of cranial irradiation, including stereotactic radiosurgery, and whole-brain radiation therapy in addition to subtotal resection of a frontal brain lesion. The patient had prolonged systemic disease control with sequential ALK inhibitors but experienced repeated intracranial progression requiring multimodal local therapies. During an acute neurological deterioration in November 2025, neuroimaging demonstrated extensive post-radiation and metastatic changes, and the differential diagnosis included tumor progression, radiation necrosis, and focal status epilepticus. Given the clinical context and imaging limitations, SMART syndrome was suspected. High-dose intravenous corticosteroids led to partial neurological improvement, supporting the diagnosis of radiation-induced cortical dysfunction. Conclusion: This case highlights the diagnostic complexity of SMART syndrome in patients with advanced metastatic brain disease and cumulative radiation exposure.

Background: Proper treatment of wounds is crucial, as untreated wounds can potentially become fatal. Ethnomedicinal herbs possess the ability to heal wounds without causing any adverse consequences, unlike chemical medications which are increasingly associated with negative effects. Hydrogels are highly promising and extensively employed in the realm of biomedicine. Hydrogel dressings have made tremendous advancements in their ability to reduce inflammation, effectively addressing many clinical problems encountered in efforts to enhance wound healing. Lupeol, a triterpene phytoconstituent, is present in numerous fruit plants and medicinal plants that have been extensively researched for its potential in treating various ailments, including skin wounds. Objective: The aim of present investigation is to assessed the wound healing efficacy of lupeol loaded hydrogel. Method: A hydrogel was synthesized by combining Carbopol 934 with HPMC polymers in a 1:1 ratio. The wound healing potential was assessed using both the excision and incision models, as well as by measuring the hydroxyproline content. Result: The excision wound study demonstrated that the H1 formulation including lupeol exhibited a substantial outcome that was comparable to the usual treatment. The duration of epithelization was determined to be 18 days. The incision wound model demonstrated that the tensile strength of H1 was much greater than the standard. The current study determined that the hydroxylproline content of formulation H1, which contains lupeol, was measured to be 43.52 +0.42, which is comparable to the standard. Conclusion: The exploration has demonstrated that the formulation has the ability to enhance the activity of wound healing. The discovery indicated that lupeol promotes the formation of new blood vessels, the expansion of fibroblast cells, and the production of cytokines and growth factors that are essential for the process of wound healing.

The population of the East Region of Cameroon lives around the forest and shares precious knowledge about the medicinal plants they possess against diseases such as COVID-19 as the role of ethno-medicine may have favored resilience against the Covid-19 pandemic in Africa. The objective of this study was to identify medicinal plants used against Covid-19 by the local population through their knowledge of COVID-19 in the East Region of Cameroon. The sociodemographic profile, information on COVID-19, the medicinal plants used against COVID-19 and the symptoms were determined. An ethnobotanical survey was conducted from November 2025 to February 2026 across twenty-five (25) villages on 500 respondents. Demographically, a large proportion of the population were men (61.6%), most of whom were non-workers (70.2%), with a dominant age group of 41 to 50 years (35%). Seventy-one percent of the population claimed to know the means of transmission, with "shaking hands with an infected person" being the most cited (41%). Meanwhile, 67% claimed to know the symptoms, with "cough" being the most mentioned (47.4%). Regarding prevention, 68.4% knew of modern prevention methods, with 24.4% favoring social distancing. 52% of the surveyed population stated they had not contracted Covid-19 (with or without testing confirmation). Majority of the population preferred traditional medicine for their health care but only 20.6% of the respondents mentioned traditional treatments against COVID-19 which may be due to the fact that only 28.6% of the respondents had a good knowledge about COVID-19. Alstonia boonei De Wild. emerged as the most used medicinal plant in traditional Covid-19 treatments by the local population, with a citation frequency of 9%. This study sheds light on how local populations perceive, adopt, and adhere to public health crisis measures.