Many public and private efforts in coming years will focus on research in precision medicine, developing biomarkers to indicate which patients are likely to benefit from a certain treatment so that others can be spared the cost--financial and physical--of being treated with unproductive therapies and therapeutic signals can be more easily uncovered. However, such research initiatives alone will not deliver new medicines to patients in the absence of strong incentives to bring new products to market. We examine the unique economics of precision medicines and associated biomarkers, with an emphasis on the factors affecting their development, pricing, and access.
AI is driving the adoption and implementation of precision medicine: an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. Think of it as a type of medical personalisation. For example, around 25,000 people in the US are diagnosed with brain tumors every year. Traditionally, they might all be given the same course of treatment to see what might work in a one-size-fits-all approach. Precision medicine will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people.
A new center at Duke University's Pratt School of Engineering will harness the power of big data to improve health care on a global scale. The Sherry and John Woo Center for Big Data and Precision Health, launched this month with more than $3 million in funding over three years from philanthropist and biotech industry executive John Woo, will support research projects, educational experiences and entrepreneurship opportunities for Duke faculty and students in collaboration with clinical and industry partners worldwide. Today, biomedical imaging and sensing technologies are gathering real-time health data at an unprecedented pace. Powerful computers can probe the complexity of entire genomes, and electronic recordkeeping offers new opportunities to analyze population-level disease patterns and issues in clinical care delivery. Across Duke, faculty and students are developing innovative data science, machine learning and digital health modeling approaches to transform this data into actionable health insights.
In order for precision medicine to be successful, accurate characterization of the patient is necessary. A variety of biomarkers could provide the necessary data, collected through a variety of'omics techniques. Add to this the complication that biomarkers may differ between population groups, or indeed between individuals, and that tracking these biomarkers as the patient's status changes can be onerous, and the future of precision medicine could be described as bleak. Yet this pessimistic outlook has not stopped researchers from pushing forward in their search for accurate and robust biomarkers, which they hope will help to predict the risk of disease, ascertain the probability of positive clinical outcomes, and evaluate therapeutic efficacy. In this supplement to Science, these important topics are discussed, with a focus on advances in precision medicine research in China.
Indeed, even 10 years back, the notice of Artificial Intelligence (AI) would refer to the dread that it would remove human employments and render them expendable. Slice to the present and that dread has now been supplanted with a progressively rational methodology where AI is being viewed as an approach to expand human capacities in an undeniably digital time. New AI frameworks have beyond-human cognitive abilities, which a significant number of us fear could conceivably dehumanize the eventual fate of work. Nonetheless, via automating these skills, AI will drive human experts up the range of abilities stepping stool into exceptionally human abilities, for example, inventiveness, social capabilities, sympathy, and sense-production, which machines can't automate. Subsequently, AI will make the working environment progressively human, not less.