Despite the surge in publications, there is a significant lack of research aiming at developing AI-driven predictive models that can streamline the drug discovery process specifically for multi-species infections, such as leishmaniasis, or even individualizing treatments based on genetic profiles. Additionally, the papers mostly focus on specific cases or mechanistic insights without addressing how to effectively integrate AI tools for real-time decision-making in drug development pipelines.
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THE OPPORTUNITY
The high volume of recent publications combined with a limited number of open roles suggests that there is a growing interest in drug discovery AI, but it may also indicate a supply-demand imbalance where the field is expanding faster than the workforce can keep up. For a researcher entering this space now, it presents a unique opportunity to carve out a niche while contributing valuable skills to an evolving and dynamic market.
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Investigate the application of machine learning algorithms to predict drug efficacy and safety for combinatorial therapies targeting leishmaniasis.
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Develop interdisciplinary models that integrate genomics, proteomics, and metabolomics data to create a holistic AI-driven drug discovery framework for personalized medicine.
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Explore real-time AI-enhanced platforms for pharmacovigilance that can automatically mine and analyze patient data to identify adverse drug reactions earlier than current methodologies.
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The localization of prostate cancer by ultrasound remains limited by the lack of B-mode conspicuity and the confinement of clinically approved microbubbles (MBs) to the vasculature. This precludes differentiating viable tumor, necrotic tissue, and margin-associated disease. We investigated prostate-specific membrane antigen (PSMA)-targeted lipid-shelled perfluorocarbon nanobubbles (PSMA-NBs) in an...
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Abstract Quantum computing has emerged as a promising paradigm for addressing computational tasks intractable for classical systems, leveraging quantum mechanical principles such as superposition and entanglement to efficiently explore high-dimensional solution spaces. In recent years, hybrid quantum-classical approaches have gained increasing attention as a means to exploit the representational p...
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Kinetoplastid diseases remain a major global health challenge, highlighting the need for new antiparasitic chemotypes. N,N′-disubstituted aliphatic diamines have emerged as a promising scaffold against trypanosomatid parasites. Building on our previous studies, we expanded the structure–activity relationship (SAR) of this chemotype through the synthesis of forty-two analogues obtained by one-pot r...
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Innate immunity provides a critical first line of defense against pathogens and homeostatic perturbations. Pattern recognition receptors detect these disruptions and initiate immune responses through multi-protein complex formation to drive inflammatory signaling and cell death pathways. Key cytosolic complexes formed by these sensors include inflammasomes and PANoptosomes. Inflammasomes induce ca...
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The persistent sensitivity to sensory and painful stimuli of people with migraine has been associated with disruption of the salience network (SN). Although migraine is characterized by severe head pain attacks, brain changes have been observed in people with migraine in between attacks (i.e., during the interictal phase). We hypothesized that SN dynamics may be altered in people with migraine dur...
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The efflux pump is one of the resistance mechanisms that has not been studied well in Iraq, especially KpnEF of Klebsiella pneumoniae. This study aimed to investigate the possible role of KpnEF active efflux in antimicrobial resistance in uropathogenic K. pneumoniae isolates. A total of 40 K. pneumoniae isolates were collected from several hospitals in Baghdad city, Al-Kindy, Ibn al-Balady, Imam A...
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Background Polycystic ovary syndrome is associated with metabolic and hormonal disturbances during pregnancy, but whether these alterations are reflected in the fetal intrauterine exposure environment remains incompletely understood. This study aimed to identify polycystic ovary syndrome-related intrauterine metabolic signatures using late-gestation amniotic fluid. Methods Untargeted metabolomic p...
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Lectins are carbohydrate-binding proteins present in nature in various plant and animal sources. Lectins have been shown to play vital roles in immunological responses, identification of pathogens, and applications in medical therapies like cancer treatment and antiviral drugs. Purity of lectins is crucial for biological activity, hence the need for efficient methods of isolation. One of the most ...
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Background Falls represent a major clinical and financial challenge for healthcare systems. Accurately predicting first falls remains challenging, especially when using routinely collected data. Objective Develop and evaluate a predictive model to identify elderly people at risk of first fall in the Basque Country using routinely collected health records. Method A retrospective study included pati...