Enabling Technologies for Personalized and Precision Medicine

Engineering approaches to precision medicine will harness population-wide data to identify individualized treatment strategies. Personalized medicine harnesses a subject’s own data to individualize their own care, from diagnosis through treatment selection and monitoring. Novel clinical trial designs will play a vital role in assessing the efficacy and safety of emerging therapies and diagnostics. Artificial intelligent platforms will globally optimize combination therapy from the preclinical through clinical stages of validation. The widespread deployment of precision and personalized medicine technologies will involve the convergence of several factors ranging from evolving education at the interface of engineering and medicine and policies that support new clinical trial designs, to scaling the use of electronic medical records (EMR) to drive clinical decision support. Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care. Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care. in the context of healthcare, AI uses algorithms to reconcile complex data in an effort to identify actionable strategies for many applications. These range from improving treatment outcomes to accelerating drug discovery, among others. with regards to healthcare, BDA is used to correlate tradeoffs and decision-making processes. For example, using BDA towards novel clinical trial designs may involve the correlation of outcome objectives for a patient with the benefits and risks undergoing treatment. this form of immunotherapy modifies a patient's own T cells, which are derived from their immune system, with chimeric antigen receptors (CAR) on their surfaces. These modified T cells can then selectively target surface markers on the cancer cells using these receptors during treatment. this cell is released by a primary tumor into the circulatory system and may serve as a foundation for metastasis. using a broad spectrum of applicable data, CDS platforms provide actionable guidance to clinicians in areas such as drug selection, dosage modifications, and other courses of treatment. the CRISPR and CRISPR-associated protein 9 (CRISPR-Cas9) platform is used for genome editing, where genetic material can be added, removed, or modified. This approach can potentially be used to address a multitude of diseases by altering the genetic information that drives the onset of these disorders. this mechanism-independent artificial intelligence platform is used to dynamically optimize clinical combination therapy dosing during the course of treatment. By using only a patient’s own data to manage their own combination therapy regimen, CURATE.AI can maximize treatment efficacy and safety for a sustained duration on an individualized basis. It is broadly applicable towards oncology, infectious disease, and many other disease indications. this is a mass spectrometry methodology that uses heavy metal antibody tags for cell surface and intracellular markers. CyTOF analysis enables multiplexed profiling of single-cell responses for applications in drug development and fundamental studies into cellular mechanisms. electronic medical records can contain a broad spectrum of information pertaining to a patient’s health history. They can serve as vital platforms for the implementation of treatment and diagnostic paradigms that may integrate emerging technologies such as artificial intelligence, wearables, and other modalities. ML platforms use algorithms that are trained with a set of data to subsequently make inferences and identify a course of action without requiring a directed set of instructions. Implementation of ML typically requires minimal human interaction. In the context of healthcare, it can be used for many applications, including the design of drug combinations and the development of biomaterials, among others. the highest dose of a drug that can be administered to a subject while simultaneously avoiding an unacceptable level of toxicity. With regards to precision and personalized medicine, emerging studies have shown promise in identifying lower drug doses that result in improved efficacy and safety, potentially avoiding the need to reach the MTD during therapy. this approach is used to address mitochondrial diseases by replacing mitochondria that contain DNA mutations with healthy mitochondria. In the context of reproductive medicine, a mother with mitochondrial disease can have her eggs transferred to a donor egg with healthy mitochondria. nanodiamonds are carbon-based nanoparticles that can be used to carry multiple classes of therapeutic and imaging compounds. Their unique surface electrostatic properties have been used to markedly improve magnetic resonance imaging contrast efficiency as well as drug delivery efficacy. this artificial intelligence-based approach uses quantifiable measures of clinical efficacy and safety, such as tumor burden through imaging or circulating biomarker analysis, as well as toxicity panels to guide drug dosing. This approach can be implemented in a mechanism-independent manner. this AI-based approach simultaneously identifies the right drugs and corresponding doses from large pools of candidate therapies for novel drug combination development. It can be implemented without disease target/mechanism information and does not rely on drug synergy predictions to optimize treatment outcomes. these nanostructures consist of precisely positioned and high-density configurations of nucleic acids that have been explored for gene regulation with broad applications across different disease indications. They are currently being evaluated at the clinical level. this approach uses 3D printed microwells that contain multiple drugs and can be used for the timed release of multiple therapies in a sustained fashion. this enzyme is comprised of DNA-binding and cleavage domains and is used as a genome editing platform. ZFN-based genome editing therapies are currently being evaluated at the clinical level.