1. El impacto de la IA generativa y la supercomputación.
La alianza entre gigantes tecnológicos y farmacéuticas está permitiendo procesar bibliotecas moleculares masivas en tiempos récord, reduciendo ciclos de investigación de años a solo meses.
- Eli lilly and nvidia are partnering to build what they call the pharmaceutical industrys most powerful supercomputer and so-called ai factory to help accelerate drug discovery and development across the sector.
- Ai just screened 325 billion molecules for potential cancer cures in days! model medicines used google clouds ai to achieve the biggest drug discovery screen ever.
- Mit researchers built boltzgen, an open-source ai that creates molecules for diseases previously considered untreatable. It collapses drug discovery timelines from years to months.
2. Avances críticos en oncología y enfermedades neurodegenerativas.
Descubrimientos recientes en nanotecnología y moléculas pequeñas prometen tratamientos mucho más potentes y específicos para el cáncer y el Alzheimer, superando las barreras de la medicina tradicional.
- New drug kills cancer 20,00x more effectively with no detectable side effects. Northwestern university scientists used nanotechnology to transform an old chemotherapy drug that kills leukemia cells while sparing healthy ones.
- Holy shit they reversed alzheimers a-beta and tau pathology in mice with a small-molecule drug! this is so much more practical than anti-amyloid antibodies or other biologics.
- Scientists prepare for clinical trials of ai-designed antibodies, ushering in a new era of drug discovery.
3. Transición hacia modelos de prueba humanos y sin animales.
La industria se aleja progresivamente de las pruebas en animales mediante el uso de organoides 3D, chips de tejido y gemelos digitales para predecir la toxicidad y eficacia con mayor precisión.
- The fda is pushing a human-first future for drug development. We spoke with greg tietjen of revalia bio on how this shift, powered by human data ai, makes trials faster, safer, and more inclusive.
- Jax aims to revolutionize drug safety testing with the cardioversea new project that combines ai, stemcells, and genetic variation to predict drugsafety before human trials.
- Fda approves new cancer drug using only human data, marking a significant milestone for nonanimal methods! qureators human vascularized organoid model improves preclinical predictability.
4. Automatización de la síntesis química y robótica.
Nuevas empresas están implementando laboratorios autónomos que utilizan robótica para eliminar el cuello de botella de la síntesis manual de moléculas.
- Onepot ai raises 13m to help make chemical drug creation easierexclusive for daniil boiko and andrei tyrin, the idea for onepot ai came from the same frustration. The best ideas in drug discovery were often blocked not by biology, but by synthesis.
- Singapores chemlex has raised 45m to build an autonomous chemistry lab where ai and robots design and run drug discovery experiments and gather data, all day long, with little input from humans.
- Medra lands 52m to advance drug discovery platform combining ai and robotics to enable continuous experimentation.
5. El potencial disruptivo de la computación cuántica.
La capacidad de las computadoras cuánticas para simular interacciones moleculares complejas promete revolucionar el diseño de fármacos personalizados y materiales biológicos.
- Quantum computings ability to simulate molecular interactions could transform life sciences and healthcare. Quantumcomputing medicalinno.
- Usc quantum technology forum highlights potential of quantum computing for drug discovery imagine a future where blockbuster drugs are designed in days, not years.
- Quantum computing and statistical thermodynamics achieve 0.76 accuracy in accelerated drug discovery with 20-fold efficiency.