Pharmacological Research’s Post

Drug combination therapy and receptor heteromerization Drug combination therapy is an alternative to conventional single-drug therapeutics when combined drugs synergize to provide more efficacious or more beneficial effects than corresponding concentrations of single drugs (X +Y > 2X or 2Y). This may happen for different diseases, being pain one of especial interest, in particular when opiates with unwanted side effects are prescribed. We have recently published an article in Biochemical Pharmacology (https://lnkd.in/djV8TM5w), in which we propose a mathematical and pharmacological framework to account for drug combination therapy in the context of GPCR heteromerization.

#BtBsPUB by Luca Sala and co-authors "Use of hiPSC-derived cardiomyocytes to study LQTS-variant specific #proarrhythmic effects of drugs" in Vascular Pharmacology, Volume 155, article 107347. Drug induced Long QT Syndrome (LQTS) occurs when drugs inadvertently block specific ion channels and cause QT interval prolongation and potentially life threatening arrhythmias as drug-induced torsades de pointes (TdP). The pro-arrhythmic potential of drugs of causing QT prolongation and TdP is currently assessed, at preclinical level, through heterologous systems and animal models. Despite these, the drug attrition rate in preclinical phases remains remarkably high, with many compounds being discarded during drug development for cardiovascular toxicity... https://lnkd.in/d5cp_Rmq #BtBsUNIMIB Università degli Studi di Milano-Bicocca

✍️Nuestro compañero Alberto Katsumiti autor del artículo "S04-04 Acute and subacute toxicity of inhaled micro- and nanoplastics using advanced In Vitro models" publicado en la revista Toxicology Letters Our colleague Alberto Katsumiti author of the article ‘S04-04 Acute and subacute toxicity of inhaled micro- and nanoplastics using advanced In Vitro models’ published in the journal Toxicology Letters https://cutt.ly/BeSsHVb7 #toxicidad #microplasticos #nanoplasticos #invitro #toxicity #microplastics #nanoplastics SAbyNA Horizon 2020

I’m super excited to share that I’ve obtained a new certification: 58th SPSR Webinar on - AI Tools For Scientific Writing & Publishing from Society of Pharmaceutical Sciences and Research (SPSR)! Honestly, it was a very productive session and it will be very much helpful for my future journey and in this booming market having an edge over AI tools is very important. By leveraging these cutting-edge tools, i will be able to focus more on innovation and discovery, while AI handles the mundane aspects of writing and publishing. #AITools #ScientificWriting #ResearchAutomation #AI #ScientificPublishing #Innovation #TechInScience #FutureOfResearch #ProfessionalGrowth #AIinResearch #SPSR #AI #IJPSR #IJP

At present, the most mature AI-based medicines are in the second phase of clinical trials, yet to be released. AI services for the life science industry demand focus on algorithms, computing power, and data. While AI companies explore algorithms, high-tech firms like NVIDIA provide computing power, data is fragmented among pharmaceutical companies, hospitals, and research institutions. The integration of resources is key to accelerating AI research in medicine. Segmented yet essential, companies like Cognizant play a vital role in commercializing AI medicines. #AI #LifeScience #MedicalResearch #DataIntegration #ArtificialIntelligence https://lnkd.in/gBiP4nBa

1. Drug discovery faces significant challenges, with only 5 out of 10,000 to 15,000 new compounds reaching clinical trials, and over 92% failing due to safety or efficacy issues. 2. The average development time for a new medicine is over a decade, often consuming a scientist's career. 3. Artificial intelligence (AI) enhances biomedical research by generating hypotheses and analyzing large data sets more efficiently than humans. 4. AI tools, like PERCEPTION, can identify patterns in cancer data, predicting treatment responses with remarkable accuracy. 5. Multidisciplinary talent is essential, as illustrated by the success of a mathematician applying AI in biomedical research. 6. AI is increasingly used in healthcare for treatment protocols, documentation, and diagnoses, leading to faster and more accurate results. 7. Public skepticism remains regarding AI in healthcare, with concerns about its impact on diagnosis and treatment outcomes, though it may reduce medical errors and biases. 8. Despite the advancements AI offers, human physicians remain irreplaceable due to their essential human qualities and judgment.

Artificial intelligence and machine learning (AI/ML) are increasingly being utilized in drug development. As your organization incorporates these new technologies, it is critical to understand their current strengths and limitations and how their use will be viewed by regulatory agencies. Join us for a webinar addressing those challenges, featuring guest presenter Dr. Qi Liu, Associate Director for Innovation & Partnership at the Office of Clinical Pharmacology/Office of Translational Sciences at the Center for Drug Evaluation and Research (CDER). Gain insights into AI/ML fundamentals, regulatory submissions at CDER/FDA, and real-world examples of review and research. Understand key challenges and regulatory considerations to effectively leverage AI/ML in drug development. Don’t miss this opportunity. Register to join us. https://lnkd.in/grFKUbu9

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides #artificial_intelligence #machine_learning #therapeutic_peptide #drug_discovery

💡 "It can now take more than a billion dollars  in funding and a decade of work to bring one new medication to market. Half of that time and money is spent on clinical trials, which are growing larger and more complex."💡 https://lnkd.in/dypZ7BjZ This recent article explores the diffrent ways AI is radically improving the clinical trial process, from study design to patient recruitment. It’s fascinating to see how the technology is helping to accelerate the development of new medications and treatments! ☝ However, even with Generative AI’s leap forward in drug discovery, obstacles persist. The industry continues to face challenges in defining molecular structures and pinpointing ideal lab products throughout the long and tedious process. At biosimulytics, we specialize in the deployment of AI for digitizing next-gen drug development. Harnessing the power of advanced AI, High Performance Computing (HPC) and quantum technologies, we're working to eliminate the bottlenecks of polymorphism and crystallization in new medicine development. Predictive insights early on= massive risk reduction in drug development, for safer, more reliable molecule forms. 💊 Stay Informed, Stay Ahead with biosimulytics! #AI #InnovationInMedicine #AIinHealthcare #DrugDevelopment #ClinicalTrials #Pharmaceuticals #biosimulytics

Artificial intelligence and machine learning (AI/ML) are increasingly being utilized in drug development. As your organization incorporates these new technologies, it is critical to understand their current strengths and limitations and how their use will be viewed by regulatory agencies. Join us for a webinar addressing those challenges, featuring guest presenter Dr. Qi Liu, Associate Director for Innovation & Partnership at the Office of Clinical Pharmacology/Office of Translational Sciences at the Center for Drug Evaluation and Research (CDER). Gain insights into AI/ML fundamentals, regulatory submissions at CDER/FDA, and real-world examples of review and research. Understand key challenges and regulatory considerations to effectively leverage AI/ML in drug development. Don’t miss this opportunity. Register to join us. https://lnkd.in/grFKUbu9