{"id":523997,"date":"2026-11-05T19:41:09","date_gmt":"2026-11-05T19:41:09","guid":{"rendered":"http:\/\/6aec916014a00a7c3c18dc30"},"modified":"2026-11-05T19:41:09","modified_gmt":"2026-11-05T19:41:09","slug":"esta-empresa-de-ia-quiere-descubrir-nuevos-medicamentos-sin-pisar-primero-el-laboratorio","status":"publish","type":"post","link":"https:\/\/sarmiento24h.com\/?p=523997","title":{"rendered":"Esta empresa de IA quiere descubrir nuevos medicamentos sin pisar primero el laboratorio"},"content":{"rendered":"<div><img decoding=\"async\" src=\"https:\/\/media.es.wired.com\/photos\/6aec91604c90e82ba0b3b605\/16:9\/w_1280,c_limit\/Business_Drug%20Discovery%20Is%20a%20Needle%20in%20a%20Haystack%20Problem.%20This%20AI%20Startup%20Thinks%20It%20Has%20The%20Answer_v1.jpg\" class=\"ff-og-image-inserted\"><\/div>\n<p>Una nueva empresa emergente brit\u00e1nica cree que la inteligencia artificial es la clave para acelerar el lento y delicado proceso de dise\u00f1o de f\u00e1rmacos.<\/p>\n<h2>Saltarse el laboratorio<\/h2>\n<p>Potential Sciences planea crear conjuntos de datos qu\u00edmicos a gran escala utilizando principios b\u00e1sicos de la f\u00edsica para simular interacciones entre \u00e1tomos, luego mol\u00e9culas peque\u00f1as y, posteriormente, amino\u00e1cidos y prote\u00ednas complejos. Con esos datos, conf\u00eda en poder entrenar modelos de IA y sistemas de predicci\u00f3n capaces de identificar f\u00e1rmacos altamente espec\u00edficos para enfermedades concretas, evitando as\u00ed la costosa y prolongada experimentaci\u00f3n en laboratorio.<\/p>\n<p>\u201cQueremos que las mol\u00e9culas que nunca van a funcionar en la cl\u00ednica fracasen r\u00e1pidamente\u201d, explica a WIRED Hatem Helal, fundador y director ejecutivo de Potential Science. \u201cEso significa contar con mejores predictores de c\u00f3mo se comportar\u00e1n al interactuar con la biolog\u00eda humana\u201d.<\/p>\n<p>La <em>startup<\/em>, lanzada el 5 de noviembre, asegura haber recibido financiamiento inicial de decenas de millones de d\u00f3lares de SovAI (el fondo de capital de riesgo para IA del gobierno brit\u00e1nico) y Twin Path Ventures, entre otros inversionistas. Los fundadores declinaron revelar la cifra exacta o la valoraci\u00f3n.<\/p>\n<p>Si las cosas se desarrollan como Potential Sciences espera, esto podr\u00eda allanar el camino para el desarrollo acelerado de nuevos tratamientos para todo tipo de enfermedades. Al reducir el costo de la experimentaci\u00f3n, Helal sostiene que el enfoque de la compa\u00f1\u00eda tambi\u00e9n podr\u00eda hacer que sea rentable para las farmac\u00e9uticas investigar medicamentos para enfermedades raras que hasta ahora no ten\u00edan tratamiento.<\/p>\n<p>\u201cQueremos que sea posible contar con <a href=\"https:\/\/es.wired.com\/articulos\/una-vacuna-experimental-logro-reducir-el-riesgo-de-recaida-melanoma\">tratamientos m\u00e1s personalizados<\/a> para las enfermedades; esta idea de que los medicamentos pueden ser combinaciones moleculares \u00fanicas adaptadas a la biolog\u00eda humana singular de cada persona\u201d, explica.<\/p>\n<p>La cuesti\u00f3n es si Potential Sciences ser\u00e1 capaz de predecir con la precisi\u00f3n que espera la capacidad de los f\u00e1rmacos candidatos para unirse a las prote\u00ednas relacionadas con la enfermedad, lo que requerir\u00eda un avance significativo.<\/p>\n<p>\u201cEstoy seguro de que supondr\u00e1 una mejora\u201d, declara Peter Wolynes, profesor de qu\u00edmica en la Universidad Rice. Sin embargo, en la actualidad, \u201cla ingenier\u00eda de prote\u00ednas est\u00e1 al nivel de los romanos, no del Renacimiento\u201d, advierte.<\/p>\n<p>Figuras destacadas del sector, como Demis Hassabis, ganador del Premio Nobel de Qu\u00edmica por su trabajo en Google DeepMind, llevan <a data-offer-url=\"https:\/\/www.wsj.com\/tech\/ai\/demis-hassabis-ai-deepmind-google-isomorphic-2b4e3153?eafs_enabled=false\" class=\"external-link\" data-event-click=\"{&quot;element&quot;:&quot;ExternalLink&quot;,&quot;outgoingURL&quot;:&quot;https:\/\/www.wsj.com\/tech\/ai\/demis-hassabis-ai-deepmind-google-isomorphic-2b4e3153?eafs_enabled=false&quot;}\" href=\"https:\/\/www.wsj.com\/tech\/ai\/demis-hassabis-ai-deepmind-google-isomorphic-2b4e3153?eafs_enabled=false\" rel=\"nofollow noopener\" target=\"_blank\">tiempo afirmando<\/a> que los avances en IA conducir\u00e1n a descubrimientos cient\u00edficos trascendentales, del mismo modo que esta tecnolog\u00eda ha <a href=\"https:\/\/es.wired.com\/articulos\/cuatro-problemas-matematicos-resueltos-con-ia-abren-un-nuevo-horizonte-humano-maquina\">revolucionado recientemente las matem\u00e1ticas<\/a>. La esperanza de <em>startups<\/em> como Potential Sciences es que el descubrimiento de f\u00e1rmacos sea una de las primeras fronteras cient\u00edficas transformadas por esta tecnolog\u00eda.<\/p>\n<h2>M\u00e1s datos<\/h2>\n<p>Actualmente, una gran proporci\u00f3n de laboratorios de descubrimiento de f\u00e1rmacos mediante IA desarrollan modelos a partir de una \u00fanica base de datos p\u00fablica de estructuras at\u00f3micas tridimensionales (el Protein Data Bank) que los investigadores han ampliado durante d\u00e9cadas con los resultados de nuevos experimentos. El problema, de acuerdo con Helal, es que el conjunto de datos sigue siendo demasiado peque\u00f1o para entrenar modelos de IA lo suficientemente avanzados como para acelerar de forma fiable la b\u00fasqueda de f\u00e1rmacos viables.<\/p>\n<p>\u201cDe todos los \u00e1tomos del universo, existen alrededor de 10<sup>\u2076\u2070<\/sup> maneras de ensamblarlos en mol\u00e9culas que potencialmente podr\u00edan administrarse a un ser humano\u201d, indica Helal. \u201cPiensa en el descubrimiento de f\u00e1rmacos como un problema de b\u00fasqueda; se trata de cu\u00e1n r\u00e1pido puede explorar y depurar ese espacio para encontrar mol\u00e9culas prometedoras para una enfermedad en particular\u201d.<\/p>\n<p>Para abordar este problema, Potential Sciences est\u00e1 intentando crear conjuntos de datos mucho m\u00e1s grandes, compuestos por datos sint\u00e9ticos generados mediante la simulaci\u00f3n de interacciones entre diferentes compuestos qu\u00edmicos. Seg\u00fan la teor\u00eda, a partir de estos conjuntos de datos mucho m\u00e1s amplios, la <em>startup<\/em> podr\u00e1 entrenar modelos de IA y sistemas de predicci\u00f3n mucho m\u00e1s avanzados.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Una nueva empresa emergente brit\u00e1nica cree que&#46;&#46;&#46;<\/p>\n","protected":false},"author":1,"featured_media":523998,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[46],"tags":[],"class_list":["post-523997","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tecnologia"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - 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