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personalized medicine
Personalized medicine or PM is a medical model that proposes the customization of healthcare, with medical decisions, practices, and/or products being tailored to the individual patient. In this model, diagnostic testing is often employed for selecting appropriate and optimal therapies based on the context of a patient’s genetic content or other molecular or cellular analysis.
The use of genetic information has played a major role in certain aspects of PM. and the term was first coined in the context of genetics, though it has since broadened to encompass all sorts of personalization measures.
Personalized medicine is not limited to pharmaceutical therapy. Advances in computational power and medical imaging are paving the way for personalized medical treatments that consider a patient’s genetic, anatomical and physiological characteristics.
Several terms, including “precision medicine,” “targeted medicine” and “pharmacogenomics” are sometimes used interchangeably with “personalized medicine.”
According to the FDA, the term is often described as providing ‘the right patient with the right drug at the right dose at the right time.’ More broadly, PM may be thought of as the tailoring of medical treatment to the individual characteristics, needs, and preferences of a patient during all stages of care, including prevention, diagnosis, treatment, and follow-up.
Advances in genetic and molecular knowledge about different diseases are widely expected to generate more opportunities for PM products and services. Clinical laboratories and pathology groups are continually developing new capabilities in molecular diagnostics, such as the analysis of DNA, RNA, and the human proteome.
Reimbursement policies will have to be redefined to fit the changes that PM will bring to the healthcare system. Some of the factors that will be considered are the level of efficacy of various genetic tests in the general population, cost-effectiveness relative to benefits, how to deal with payment systems for extremely rare conditions, and how to redefine the insurance concept of “shared risk” to incorporate the effect of the newer concept of “individual risk factors.”
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Volume XXXII, No. 1 – January 6, 2025
The Dark Report examines how AI is being used to predict the outcomes of FDA LDT lawsuits. Also, this issue is Part Two of a series about boosting pathology compensation in different settings, including hospitals. Two experienced pathology consultants identify the most effective approaches when negotiating Part A pathology agreements with hospitals and health systems, along with how to use data to bolster these negotiations.
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