Inappropriate modeling of chronic and complex disorders: How to reconsider the approach in the context of predictive, preventive and personalized medicine, and translational medicine
- PMID: 31462938
- PMCID: PMC6695463
- DOI: 10.1007/s13167-019-00176-z
Inappropriate modeling of chronic and complex disorders: How to reconsider the approach in the context of predictive, preventive and personalized medicine, and translational medicine
Abstract
Preclinical investigations such as animal modeling make the basis of clinical investigations and subsequently patient care. Predictive, preventive, and personalized medicine (PPPM) not only highlights a patient-tailored approach by choosing the right medication, the right dose at the right time point but it as well essentially requires early identification, by the means of complex and state-of-the-art technologies of unmanifested pathological processes in an individual, in order to deliver targeted prevention early enough to reverse manifestation of a pathology. Such an approach can be achieved by taking into account clinical, pathological, environmental, and psychosocial characteristics of the patients or an individual who has a suboptimal health condition. Inappropriate modeling of chronic and complex disorders, in this context, may diminish the predictive potential and slow down the development of PPPM and consequently modern healthcare. Therefore, it is the common goal of PPPM and translational medicine to find the solution for the problem we present in our review. Both, translational medicine and PPPM in parallel, essentially need accurate surrogates for misleading animal models. This study was therefore undertaken to provide shreds of evidence against the validity of animal models. Limitations of current animal models and drug development strategies based on animal modeling have been systematically discussed. Finally, a variety of potential surrogates have been suggested to change the unfavorable situation in medical research and consequently in healthcare.
Keywords: Animal modeling; Cancer; Cardiovascular disorders; Chronic diseases; Clinical trial failure; Disease modeling; Drug development; Drug discovery; Future healthcare; Predictive preventive personalized medicine; Toxicology; Translational medicine.
Conflict of interest statement
Competing interestsThe authors declare that they have no competing interests.
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