27:
259:. The alliance included a $ 180 million equity investment, and a $ 90 million discovery and development partnership focused on Sanofiâs oncology efforts in four different cancers. Sanofi used Owkinâs technology to find new biomarkers and therapeutic targets, build prognostic models, and predict response to treatment.
187:
project, an initiative that included Owkin, 10 pharmaceutical companies, and six other partners, applied federated learning to train AI on datasets without having to share proprietary data. The aim was to improve drug discovery and they built a shared platform called MELLODDY (Machine
Learning Ledger
217:
diagnosis and treatment. It screens patients for microsatellite instability (MSI), which is a key genomic biomarker in colorectal cancer. MSIntuit CRC is approved for use across the
European Union. It underwent a blind validation in 2023, made possibly partly by its availability within Medipath, the
199:
is a machine learning technique that allows a model pre-trained on one task to be used on another related task. Owkin uses transfer learning to work on very small datasets. Owkin's model (CHOWDER) is able to understand high-level graphic patterns, such as tumors, that are themselves relying on very
147:, a type of privacy preserving technology, to access multimodal patient data from academic institutions and hospitals to train its AI models for drug discovery, development, and diagnostics. Owkin has collaborated with pharmaceutical companies around the world to improve their therapeutic programs.
1028:
Courtiol, Pierre; Maussion, Charles; Moarii, Matahi; Pronier, Elodie; Pilcer, Samuel; Sefta, Meriem; Manceron, Pierre; Toldo, Sylvain; Zaslavskiy, Mikhail; Le Stang, Nolwenn; Girard, Nicolas; Elemento, Olivier; Nicholson, Andrew G.; Blay, Jean-Yves; Galateau-Sallé, Françoise (October 2019).
1160:
Saillard, Charlie; Delecourt, Flore; Schmauch, Benoit; Moindrot, Olivier; Svrcek, Magali; Bardier-Dupas, Armelle; Emile, Jean
Francois; Ayadi, Mira; Rebours, Vinciane; de Mestier, Louis; Hammel, Pascal; Neuzillet, Cindy; Bachet, Jean Baptiste; Iovanna, Juan; Dusetti, Nelson (2023-06-13).
267:
In June 2022, Owkin entered a strategic alliance with
Bristol-Myers Squibb to help them design potentially more precise and efficient clinical trials. The collaboration initially focused on cardiovascular disease, and has the potential to expand into projects in other therapeutic areas.
1120:
Ogier du
Terrail, Jean; Leopold, Armand; Joly, Clément; Béguier, Constance; Andreux, Mathieu; Maussion, Charles; Schmauch, Benoßt; Tramel, Eric W.; Bendjebbar, Etienne; Zaslavskiy, Mikhail; Wainrib, Gilles; Milder, Maud; Gervasoni, Julie; Guerin, Julien; Durand, Thierry (January 2023).
1260:
Saillard, Charlie; Schmauch, Benoit; Laifa, Oumeima; Moarii, Matahi; Toldo, Sylvain; Zaslavskiy, Mikhail; Pronier, Elodie; Laurent, Alexis; Amaddeo, Giuliana; Regnault, HélÚne; Sommacale, Daniele; Ziol, Marianne; Pawlotsky, Jean-Michel; Mulé, Sébastien; Luciani, Alain (December 2020).
1210:
Saillard, Charlie; Dubois, Rémy; Tchita, Oussama; Loiseau, Nicolas; Garcia, Thierry; Adriansen, Aurélie; Carpentier, Séverine; Reyre, Joelle; Enea, Diana; von Loga, Katharina; Kamoun, Aurélie; Rossat, Stéphane; Wiscart, Corentin; Sefta, Meriem; Auffret, Michaël (2023-11-06).
719:
Saillard, Charlie; Dubois, Rémy; Tchita, Oussama; Loiseau, Nicolas; Garcia, Thierry; Adriansen, Aurélie; Carpentier, Séverine; Reyre, Joelle; Enea, Diana; von Loga, Katharina; Kamoun, Aurélie; Rossat, Stéphane; Wiscart, Corentin; Sefta, Meriem; Auffret, Michaël (2023-11-06).
346:
1030:
1068:
Schmauch, Benoßt; Romagnoni, Alberto; Pronier, Elodie; Saillard, Charlie; Maillé, Pascale; Calderaro, Julien; Kamoun, Aurélie; Sefta, Meriem; Toldo, Sylvain; Zaslavskiy, Mikhail; Clozel, Thomas; Moarii, Matahi; Courtiol, Pierre; Wainrib, Gilles (2020-08-03).
179:
Owkin uses federated learning, a decentralized machine learning technique, to train machine learning models with multiple data providers. Federated learning allows data providers to collaborate without moving or sharing their data.
276:
In
December 2023, Owkin entered a strategic alliance with MSD to develop and commercialize AI-powered digital pathology diagnostics for the EU market that could be used to identify patients suitable for
341:
Owkinâs research on AI/ML has led to a number of publications that focus on machine learning methodologies and the development of predictive models for different disease areas, mainly oncology.
449:
773:
162:
Owkin has raised over $ 255 million and became a âunicornâ â a startup valued at more than $ 1 billion â in
November 2021 through a $ 180 million investment from French biopharma company
326:
230:
patients will relapse within a few years of initial treatment. It is used by pathologists and oncologists to help determine the right treatment pathway for breast cancer patients.
333:. It uses spatial omics, multimodal patient data, and artificial intelligence, and aims to âoffer unprecedented information on the structure of tumorsâ and guide new treatments.
884:
639:
476:
293:
started a multi-year partnership focused on developing âbetter-targeted therapiesâ in oncology and other disease areas. The partnershipâs first two projects were in
838:
578:
525:
1410:
861:"Exclusive: Medical AI startup Owkin just secured $ 80 million as it gears up to enhance drug trials with the pharmaceutical giant Bristol Myers Squibb"
330:
695:
1351:
1004:
550:
1327:
611:
1415:
1262:
155:
Owkin was founded in 2016, by Thomas Clozel, a clinical research doctor and son of Jean-Paul and
Martine Clozel founders of Swiss biotech
860:
1163:"Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma"
802:
368:âPacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinomaâ
403:
2021 Member
Recognition Awards from the French American Chamber of Commerce - Technology, Startups & Entrepreneurs Committee Awards
820:
450:"French AI biotech unicorn Owkin has launched a âŹ33 million AI-powered precision medicine project for cancer diagnosis and treatment"
1405:
1301:
898:
666:
381:
322:
922:
1123:"Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer"
361:âFederated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer"
1213:"Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides"
722:"Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides"
375:âValidation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slidesâ
949:
976:
314:
640:"Major pharma companies, including Novartis and Merck, build federated learning platform for drug discovery"
310:
140:
294:
1263:"Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides"
1302:"3 informations pour bien commencer la journée : Chaire Good In Tech, les Rebondisseurs, et Owkin"
382:
Predicting
Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides
290:
774:"Owkin's AI Diagnostic for Colorectal Cancer Takes Center Stage with Promising Validation Results"
143:
to identify new treatments, optimize clinical trials and develop AI diagnostics. The company uses
188:
Orchestration for Drug Discovery). The first results of the project were published in July 2022.
144:
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500:
360:
1031:"Deep learning-based classification of mesothelioma improves prediction of patient outcome"
347:âDeep learning-based classification of mesothelioma improves prediction of patient outcomeâ
136:
1245:
1195:
1071:"A deep learning model to predict RNA-Seq expression of tumours from whole slide images"
1005:"Owkin invests $ 50M in spatial omics project that will 'revolutionize cancer research'"
754:
354:âA deep learning model to predict RNA-Seq expression of tumours from whole slide imagesâ
1377:"2021 Member Recognition Awards Recognize Impactful Initiatives in the FACC-NY Network"
1105:
318:
1399:
1212:
1162:
1122:
1070:
721:
612:"L'apprentissage fédéré, le futur de la médecine basée sur les données - mind Health"
423:
374:
367:
353:
278:
227:
37:
551:"Sanofi exec jumps to Owkin to ramp up the AI biotech's pharma partnership plans"
1228:
1178:
1138:
1087:
737:
213:
MSIntuit CRC is an AI-powered digital pre-screening diagnostic tool to improve
200:
low-level visual patterns, in order to fully learn the tumor's visual pattern.
1046:
26:
1286:
1236:
1186:
1146:
1096:
1054:
745:
803:"Owkin AI for identifying breast, colorectal cancer types score EU approval"
821:"Sanofi inks $ 270M cancer AI deal with R&D platform developer Owkin"
156:
1278:
256:
244:
309:
MOSAIC (Multi Omic Spatial Atlas in Cancer) was formed by Owkin,
1352:"Tech For Good Awards: découvrez les gagnants de l'édition 2021"
1328:"Prix Galien Nominees for Best Digital Health Product Announced"
696:"OWKIN secures $ 11m to scale AI-driven drug discovery platform"
247:
to test the ability of AI to improve cardiovascular prediction.
839:"Drugmaker Sanofi invests $ 180 mln in French AI startup Owkin"
526:"Drugmaker Sanofi invests $ 180 mln in French AI startup Owkin"
477:"Amgen, Owkin Use AI to Improve Cardiovascular Risk Prediction"
356:, Nature Communications volume 11, Article number: 3877 (2020)
159:, and Gilles Wainrib, a professor of Artificial Intelligence.
667:"Federated Learning Can Protect Patients' Data In Hospitals"
424:"AI Steps Up to Streamline MSI Testing in Colorectal Cancer"
950:"Owkin signs up another pharma partner for its AI platform"
923:"Owkin and MSD join forces on AI-powered digital pathology"
899:"BMS Enlists Owkin's AI/ML Tech to Improve Clinical Trials"
397:
2020 Galien Foundation Best Digital Health Product Nominee
163:
1306:
Maddyness - Le média pour comprendre l'économie de demain
255:
In November 2021 Owkin entered a strategic alliance with
977:"ASCO: AI-powered MOSAIC will build 3D atlas for cancer"
102:
AI Drug Discovery, AI Drug Development, AI Diagnostics
121:
116:
106:
98:
90:
80:
66:
58:
43:
33:
327:Friedrich-Alexander-UniversitĂ€t Erlangen-NĂŒrnberg
778:GEN - Genetic Engineering and Biotechnology News
579:"Federated Learning Explained Simply - Nanalyze"
400:2021 Tech For Good Awards - âHealthâ category
8:
883:: CS1 maint: multiple names: authors list (
19:
86:US, France, UK, Switzerland, Germany, Spain
25:
18:
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218:largest pathology lab network in France.
363:Nat Med (2023). 10.1038/s41591-022-02155
1326:Hamilton-Basich, Melanie (2020-10-05).
412:
998:
996:
971:
969:
944:
942:
876:
226:Dx RlapsRisk BC uses AI to predict if
1003:outsourcing-pharma.com (2023-06-08).
854:
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797:
795:
793:
767:
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694:outsourcing-pharma.com (2018-02-15).
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377:Nature Communications 14, 6695 (2023)
7:
859:Burroughs, Tasmin Lockwood, Callum.
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505:Basel Area Business & Innovation
471:
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331:Charité-UniversitÀtsmedizin Berlin
14:
1411:Artificial intelligence companies
524:Rosemain, Mathieu (2021-11-18).
349:, Nat Med 25, 1519â1525 (2019)
1:
1416:Companies established in 2016
549:Vinluan, Frank (2022-10-04).
359:Jean Ogier du Terrail et al.
62:Thomas Clozel, Gilles Wainrib
1300:Maignan, Iris (2019-09-13).
772:Thomas, Uduak (2023-11-10).
638:Wiggers, Kyle (2020-09-17).
448:Alston, Fiona (2023-03-31).
394:2019 AI For Health challenge
323:Lausanne University Hospital
315:the University of Pittsburgh
289:In October 2023, Owkin and
1432:
1229:10.1038/s41467-023-42453-6
1179:10.1038/s41467-023-39026-y
1139:10.1038/s41591-022-02155-w
1088:10.1038/s41467-020-17678-4
738:10.1038/s41467-023-42453-6
370:Nat Commun 14, 3459 (2023)
94:MSIntuit CRC, RlapsRisk BC
1047:10.1038/s41591-019-0583-3
24:
352:Schmauch, BenoĂźt et al.
345:Courtiol, Pierre et al.
243:Owkin collaborated with
47:August 3, 2016
1406:Biotechnology companies
577:Nanalyze (2020-01-27).
325:, Uniklinikum Erlangen/
311:Nanostring Technologies
141:artificial intelligence
1009:outsourcing-pharma.com
700:outsourcing-pharma.com
501:"Owkin heads to Basel"
384:" Hepatology 72 (2020)
295:translational medicine
16:French medical company
1217:Nature Communications
1167:Nature Communications
1075:Nature Communications
726:Nature Communications
204:Products and Services
671:The Medical Futurist
263:Bristol-Myers Squibb
108:Number of employees
21:
380:Saillard et al., "
175:Federated learning
145:federated learning
1279:10.1002/hep.31207
1041:(10): 1519â1525.
373:Saillard et al.,
366:Saiilard et al.,
299:digital pathology
215:colorectal cancer
197:Transfer learning
192:Transfer learning
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137:biotech company
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1133:(1): 135â146.
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1384:. Retrieved
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1356:BFM BUSINESS
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673:. 2021-04-13
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555:MedCity News
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