Michael S Ringel, Julie Dethier, Michelle J. Davitt, Maria Denslow, R. Andrew Fowler, Sebastian C. Hasenfuss, Ulrik Schulze
{"title":"怎样才能使疾病取得进展?","authors":"Michael S Ringel, Julie Dethier, Michelle J. Davitt, Maria Denslow, R. Andrew Fowler, Sebastian C. Hasenfuss, Ulrik Schulze","doi":"10.1101/2024.02.27.24303441","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate what conditions need to be in place to make progress in combating a disease using a case-control design: we compare cases (diseases with a successful therapy) to controls (diseases without a successful therapy). We find five conditions ('hurdles') must typically be cleared for success: (A) understanding of biological drivers, (B) ability to modulate biology, (C) availability of translational models, (D1) ability to identify patients, and (D2) ability to measure clinical response. This framework is similar to ones deployed to evaluate individual drug candidates but is employed here to make inferences about entire diseases. It can be used to identify diseases most ready for progress, where efforts should be focused to make progress in diseases that are currently intractable, and where the industry could benefit from development of tools to address the hurdle that is most commonly the last to be cleared across diseases-namely, (C) translational models.","PeriodicalId":501447,"journal":{"name":"medRxiv - Pharmacology and Therapeutics","volume":"51 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What does it take to make progress in a disease?\",\"authors\":\"Michael S Ringel, Julie Dethier, Michelle J. Davitt, Maria Denslow, R. Andrew Fowler, Sebastian C. Hasenfuss, Ulrik Schulze\",\"doi\":\"10.1101/2024.02.27.24303441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate what conditions need to be in place to make progress in combating a disease using a case-control design: we compare cases (diseases with a successful therapy) to controls (diseases without a successful therapy). We find five conditions ('hurdles') must typically be cleared for success: (A) understanding of biological drivers, (B) ability to modulate biology, (C) availability of translational models, (D1) ability to identify patients, and (D2) ability to measure clinical response. This framework is similar to ones deployed to evaluate individual drug candidates but is employed here to make inferences about entire diseases. It can be used to identify diseases most ready for progress, where efforts should be focused to make progress in diseases that are currently intractable, and where the industry could benefit from development of tools to address the hurdle that is most commonly the last to be cleared across diseases-namely, (C) translational models.\",\"PeriodicalId\":501447,\"journal\":{\"name\":\"medRxiv - Pharmacology and Therapeutics\",\"volume\":\"51 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Pharmacology and Therapeutics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.02.27.24303441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Pharmacology and Therapeutics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.02.27.24303441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we investigate what conditions need to be in place to make progress in combating a disease using a case-control design: we compare cases (diseases with a successful therapy) to controls (diseases without a successful therapy). We find five conditions ('hurdles') must typically be cleared for success: (A) understanding of biological drivers, (B) ability to modulate biology, (C) availability of translational models, (D1) ability to identify patients, and (D2) ability to measure clinical response. This framework is similar to ones deployed to evaluate individual drug candidates but is employed here to make inferences about entire diseases. It can be used to identify diseases most ready for progress, where efforts should be focused to make progress in diseases that are currently intractable, and where the industry could benefit from development of tools to address the hurdle that is most commonly the last to be cleared across diseases-namely, (C) translational models.