[미국 기업] 1. 타겟 발굴 (질병 원인 찾기) ✅인실리코 메디신 (Insilico Medicine) 방식: 수조 개의 생물학 데이터를 분석해 '병을 일으키는 단백질'을 빠르게 특정. 효과: 수년이 걸리던 탐색 과정을 수개월로 단축. 2. 약물 설계 (가상 분자 만들기) ✅아톰와이즈 (Atomwise) 방식: 'AtomNet(딥러닝)'이 수십억 개의 화합물 중 타겟에 딱 맞는 물질을 예측. 효과: 실험실에서 직접 만들지 않고도 컴퓨터상에서 최적의 후보를 선별. ✅슈뢰딩거 (Schrödinger) 방식: 물리 법칙을 적용해 분자가 어떻게 결합할지 정밀 시뮬레이션. 효과: 실제 합성 전 약물의 효능과 독성을 미리 정확하게 계산. 3. 검증 및 실험 (자동화로 확인하기) ✅리커전 파마슈티컬스 (Recursion) 방식: 로봇이 세포 실험을 하고, AI가 찍은 사진(이미지)으로 약물 반응을 분석. 효과: 인간이 놓치는 미세한 세포 변화를 감지하여 유효물질 도출. ✅엑셀라 바이오시스템즈 (Xellar) 방식: 인체 장기를 모사한 칩(Chip) 위에서 AI가 약물 반응을 실시간 모니터링. 효과: 동물 실험보다 정확하게 인체 독성 여부를 미리 확인. [한국 기업] 1. 종합 플랫폼 (후보물질 도출 및 최적화) ✅신테카바이오 (Syntekabio) 방식: 자체 슈퍼컴퓨터 인프라와 ‘딥매처’ 플랫폼으로 단백질과 약물이 결합하는 전 과정을 시뮬레이션. 효과: 실험 전 가상 공간에서 후보물질을 먼저 걸러내어 물질 발굴 속도를 3~4배 높임. ✅파로스아이바이오 (Pharos iBio) 방식: '케미버스'를 활용해 희귀질환 타겟과 약물의 상호작용 및 심장 독성을 미리 예측. *케미버스: AI·시뮬레이션·빅데이터를 활용해 ‘가상의 화학 세계’를 만들고 그 안에서 신약 후보 물질을 탐색·설계·검증하는 개념 효과: AI로 찾은 급성 골수성 백혈병 치료제가 실제 글로벌 임상 1상에서 효능을 입증 중. 2. 타겟 발굴 및 전주기 혁신 ✅스탠다임 (Standigm) 방식: 딥러닝으로 수많은 생물학적 경로를 학습해 질병의 '핵심 타겟'을 찾고 최적의 분자 구조를 직접 설계. 효과: 타겟 발굴부터 후보물질 확보까지 전 과정을 자동화하여 수개월 내에 특허 가능한 물질 도출. 3. 약물 재창출 및 적응증 확장 ✅온코크로스 (Oncocross) 방식: ‘랩터 AI’가 질병의 유전자 발현 패턴(전사체)을 분석해, 기존에 시판 중인 약이 다른 병에도 효과가 있는지 분석. 효과: 이미 안전성이 검증된 약을 활용하므로 개발 기간을 획기적으로 줄이고 성공률을 극대화. 4. 공간 생물학 기반 정밀 분석 ✅포트래이 (Portrai) 방식: 암세포가 조직 어디에 위치하는지 보여주는 ‘공간 전사체’ 데이터에 AI를 결합해 분석. 효과: 약물이 암세포까지 도달하는 경로를 정확히 예측하여 차세대 항암제(ADC 등)의 타겟을 정밀하게 발굴.

Atomwise’s patented AI technology AtomNet can analyze billions of compounds and screen challenging target proteins in the small molecule drug discovery process. canvasbusinessmodel.com/blog… Pfizer, Inc. X Atomwise, Inc. September 17, 2018 -- Atomwise Inc., a leader in Artificial Intelligence (AI) for drug discovery and design, has entered into an evaluation agreement with Pfizer Inc. (NYSE: PFE). Pfizer will evaluate Atomwise’s platform to identify potential drug candidates for up to three target proteins selected by Pfizer. In the agreement, Pfizer will pay a technology access fee and additional success-based payments for each target protein of interest. Atomwise will computationally analyze millions of diverse small molecules for each of Pfizer’s identified target proteins using its cutting-edge AI platform to predict those that may bind with high affinity to the selected target proteins. Atomwise’s medicinal and computational chemistry teams will also work with Pfizer scientists to define the required potency and other chemical properties of the small molecules for the targets of interest. pfizer.com/news/press-releas… Charles River Laboratories International, Inc. X Atomwise, Inc. Jan. 11, 2019-- Charles River Laboratories International, Inc. (NYSE: CRL) and Atomwise, Inc. today announced the formation of a strategic alliance that offers clients access to Atomwise’s artificial intelligence (AI)-powered, structure-based, drug design technology, which allows scientists to predict how well a small molecule will bind to a target protein of interest. By removing sole reliance on empirical screening, AI enables drug researchers to test an extremely large and diverse chemical space in a matter of days and move through the optimization process quickly by focusing only on those compounds predicted to have improved target-binding attributes. ir.criver.com/news-releases/…

#AI is revolutionizing drug discovery! Platforms like AtomNet enhance drug design by predicting molecule interactions, and streamlining development. Learn how AI is transforming #LifeSciences in our latest blog: trinus.com/5-digital-transfo… #DigitalTransformation #HealthTech

We participated in @AtomwiseInc #AIMS study published in @SciReports highlighting #AtomNet as a viable alternative to high-throughput screening! Read about the largest and most comprehensive virtual HTS campaign to date: atomwise.com/2024/04/02/pres… #drugdiscovery #AI #pharma #biotech

Excited to be part of @Atomwise's landmark paper in @Nature Scientific Reports highlighting the results of the AIMS initiative that establish the AtomNet #AI platform as a viable alternative to HTS for #DrugDiscovery nature.com/articles/s41598-0…

Excited to be part of @Atomwise's landmark paper in Nature Scientific Reports highlighting the results of the AIMS initiative that establish the AtomNet #AI platform as a viable alternative to high-throughput screening (HTS) for #DrugDiscovery. nature.com/articles/s41598-0…

We participated in @AtomwiseInc #AIMS study published in @SciReports highlighting #AtomNet as a viable alternative to high-throughput screening.  nature.com/articles/s41598-0… #AI #pharma #biotech

We are glad to be part of the global consortium, The @AtomwiseInc AIMS Program where we contributed by identifying new antileishmanial proteasome 20S inhibitors. The landmark paper was published today in @SciReports #Fiocruz #drudiscovery #AI #AtomNet nature.com/articles/s41598-0…

Thankful to have participated in this tour de force undertaken by @AtomwiseInc in @SciReports highlighting #AtomNet as an alternative to high-throughput screening! The largest and most comprehensive virtual HTS campaign to date! atomwise.com/2024/04/02/pres… #drugdiscovery #AI #biotech

We participated in @AtomwiseInc #AIMS study published in @SciReports highlighting #AtomNet as a viable alternative to high-throughput screening: atomwise.com/2024/04/02/pres… #drugdiscovery #AI #pharma #biotech

We participated in @AtomwiseInc #AIMS study published in @SciReports highlighting #AtomNet as an alternative to high-throughput screening! Read about the largest virtual HTS campaign to date: atomwise.com/2024/04/02/pres… #drugdiscovery #AI @NEH_CVRTI @RobinShawCVRTI @StavrosDrakos

We participated in @AtomwiseInc #AIMS study published in @SciReports highlighting #AtomNet as a viable alternative to high-throughput screening! Read about the largest and most comprehensive virtual HTS campaign to date: atomwise.com/2024/04/02/pres… #drugdiscovery #AI #pharma #biotech

Staff Software Engineer Tiffany Williams @Atomwiseinc discusses the drug discovery process with AtomNet @MosaicML Girl Geek Dinner. youtube.com/watch?v=o0svRi22…

"Internet" never officially comes back but we have massive eathernet servers run by the global polarities Future atompunk civilization creates Atomnet™ (no one's entirely sure how it works)

Artificial Intelligence is transforming the pharmaceutical industry. 🚀 Our Top 5 AI-focused biotech companies transforming drug discovery: 1⃣ Insilico Medicine's Pharma.AI is expediting target discovery & trial management. Dive in at insilico.com 2⃣ BenevolentAI's platform integrates data for a comprehensive biology view, driving insights at benevolent.ai 3⃣ Atomwise's AtomNet expands the horizons of drug discovery with innovative techniques. Explore atomwise.com 4⃣ Recursion Pharmaceuticals fuses technology & biology to revolutionize therapeutics. Learn more at recursionpharma.com 5⃣ Exscientia's patient-first AI approach prioritizes patient data for improved outcomes. Visit exscientia.ai These trailblazers are speeding up the journey from lab to pharmacy, preparing us for a new era of AI-propelled pharmaceutical research. 🧪🧬🔬 Find out more at scisummary.com/blog/34-the-f…

El descubrimiento de fármacos implica ensayos clínicos de miles de horas de trabajo, costando un promedio de $1.3 billones. 👉🏼 Solo el 10% de esos medicamentos se llevan con éxito al mercado. AtomNet de @AtomwiseInc utiliza la AI en el diseño y desarrollo de medicamentos 💊

Like image recognition technology finds faces, @DCVC company @AtomwiseInc's #AtomNet technology finds small molecule hits for undruggable targets to design better medicines, faster. #TargetTheImpossible #DrugDiscovery atomwise.com/how-we-do-it/

Atomwise is leveraging its AtomNet® platform for computational discovery & research via its newly announced research collaboration with Sanofi. @DCVC company @AtomwiseInc helps create better medicines faster with AI-powered #DrugDiscovery. atomwise.com/2022/08/17/atom…

Staff Software Engineer Tiffany Williams @Atomwiseinc discusses the drug discovery process with AtomNet @MosaicML Girl Geek Dinner. youtube.com/watch?v=o0svRi22…