In making a credible business case for investors and industry stakeholders to view personalized medicine as a viable business model, we not only must create excitement in the promise of personalized medicine, but also must find viable alternatives in addressing the barriers or risks surrounding the biomedical discovery and development models of today. Some of the risks we identify include IP issues, difficulties in validating targets, ability to rapidly achieve proof of concept, navigating the famed "Valley of Death," and inefficiencies in the current clinical development process, as well as the need for new industry business models that predict an attractive return on investment. In this paper; however, we limit our discussion to the potential for personalized medicine to create efficiencies in the preclinical and clinical phases of drug innovation and generate economic returns. We also introduce unique industry collaboration mechanisms with nonprofit disease-focused organizations that serve an important role in de-risking aspects of drug discovery and clinical development in their respective disease sectors, as well as bridging early-stage funding needs. These collaborations and de-risking strategies could provide an important model for the further development and growth of the personalized medicine sector. With respect to definition, we shall use the more general term "stratified medicine," of which personalized medicine is the individualized member of a spectrum that includes empirical medicine, stratified medicine, and personalized medicine. In the latter two, a biomarker is critical in identifying sub-populations or strata of patients that can benefit from a therapeutic intervention that is related to that biomarker, or develops a therapy that specifically benefits an individual who possesses that biomarker. A biomarker also may identify strata of patients that might be susceptible to side effects from a particular therapy.
{"title":"Assessing Risk and Return: Personalized Medicine Development & New Innovation Paradigm","authors":"F. Douglas, Lesa Mitchell","doi":"10.2139/ssrn.1295507","DOIUrl":"https://doi.org/10.2139/ssrn.1295507","url":null,"abstract":"In making a credible business case for investors and industry stakeholders to view personalized medicine as a viable business model, we not only must create excitement in the promise of personalized medicine, but also must find viable alternatives in addressing the barriers or risks surrounding the biomedical discovery and development models of today. Some of the risks we identify include IP issues, difficulties in validating targets, ability to rapidly achieve proof of concept, navigating the famed \"Valley of Death,\" and inefficiencies in the current clinical development process, as well as the need for new industry business models that predict an attractive return on investment. In this paper; however, we limit our discussion to the potential for personalized medicine to create efficiencies in the preclinical and clinical phases of drug innovation and generate economic returns. We also introduce unique industry collaboration mechanisms with nonprofit disease-focused organizations that serve an important role in de-risking aspects of drug discovery and clinical development in their respective disease sectors, as well as bridging early-stage funding needs. These collaborations and de-risking strategies could provide an important model for the further development and growth of the personalized medicine sector. With respect to definition, we shall use the more general term \"stratified medicine,\" of which personalized medicine is the individualized member of a spectrum that includes empirical medicine, stratified medicine, and personalized medicine. In the latter two, a biomarker is critical in identifying sub-populations or strata of patients that can benefit from a therapeutic intervention that is related to that biomarker, or develops a therapy that specifically benefits an individual who possesses that biomarker. A biomarker also may identify strata of patients that might be susceptible to side effects from a particular therapy.","PeriodicalId":119507,"journal":{"name":"Kauffman: Other (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although data from the Administrative Office (AO) of the U.S. Courts suggest that only a small fraction of the 1.6 million bankruptcies filed each year are business failures, new research from the Consumer Bankruptcy Project reveals that roughly 17 percent of bankruptcy filings involve the failure of a business. First, the AO's count of the number of business bankruptcy filings is discussed in light of figures from datasets that directly contradict the AO data. It is then argued that attorneys' tendency to misclassify bankruptcy cases filed with automated form software systematically skews the AO data so that fewer cases are reported than actually exist. Data gathered from a 2001 survey of 1,771 Chapter 7 and Chapter 13 filers, 911 of whom were interviewed by telephone, suggest that AO figures vastly undercount the percentage of bankruptcy filers with a failed business. In fact, nearly 99 percent of the debtors in the survey sample who were identified as business owners appeared in the AO data as non-business cases. An apparent downward trend in business bankruptcies in recent years appears to be inaccurate. It is noted that the tremendous inaccuracy of the government's data on business bankruptcies has implications for bankruptcy policy and legislation.
{"title":"The Myth of the Disappearing Business Bankruptcy","authors":"Robert M. Lawless, E. Warren","doi":"10.15779/Z384X5Q","DOIUrl":"https://doi.org/10.15779/Z384X5Q","url":null,"abstract":"Although data from the Administrative Office (AO) of the U.S. Courts suggest that only a small fraction of the 1.6 million bankruptcies filed each year are business failures, new research from the Consumer Bankruptcy Project reveals that roughly 17 percent of bankruptcy filings involve the failure of a business. First, the AO's count of the number of business bankruptcy filings is discussed in light of figures from datasets that directly contradict the AO data. It is then argued that attorneys' tendency to misclassify bankruptcy cases filed with automated form software systematically skews the AO data so that fewer cases are reported than actually exist. Data gathered from a 2001 survey of 1,771 Chapter 7 and Chapter 13 filers, 911 of whom were interviewed by telephone, suggest that AO figures vastly undercount the percentage of bankruptcy filers with a failed business. In fact, nearly 99 percent of the debtors in the survey sample who were identified as business owners appeared in the AO data as non-business cases. An apparent downward trend in business bankruptcies in recent years appears to be inaccurate. It is noted that the tremendous inaccuracy of the government's data on business bankruptcies has implications for bankruptcy policy and legislation.","PeriodicalId":119507,"journal":{"name":"Kauffman: Other (Topic)","volume":"506 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116329865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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