Editing AI for Personalized Medicine (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Precision medicine''' — Medical care tailored to the individual based on their unique genetic, molecular, and lifestyle profile.
* '''Biomarker''' — A measurable biological indicator (genetic variant, protein level, imaging feature) predicting disease risk, diagnosis, or treatment response.
* '''Pharmacogenomics''' — How genetic variation affects drug metabolism and response; the foundation of drug personalization.
* '''Companion diagnostic''' — An FDA-approved diagnostic test paired with a specific drug to identify patients who will benefit.
* '''Tumor mutational burden (TMB)''' — A biomarker predicting immunotherapy response across cancer types.
* '''HLA typing''' — Identifying human leukocyte antigen variants that predict drug hypersensitivity reactions and transplant compatibility.
* '''Multi-omics''' — Integrating genomics, transcriptomics, proteomics, metabolomics, and microbiomics for comprehensive patient profiling.
* '''Patient stratification''' — Dividing patients into subgroups with different predicted responses to guide treatment decisions.
* '''Predictive biomarker''' — Predicts response to a specific treatment (vs. prognostic biomarker, which predicts disease outcome regardless of treatment).
* '''Liquid biopsy''' — Blood test detecting circulating tumor DNA or cells; enables non-invasive personalized tumor monitoring.
* '''Digital twin (personalized medicine)''' — A computational model of an individual patient for simulating treatment responses.
* '''N-of-1 trial''' — A clinical trial with a single patient cycling through treatments to determine individual optimal therapy.
* '''Polygenic risk score (PRS)''' — ML-derived score from thousands of genetic variants predicting individual disease risk.
* '''Wearable integration''' — Using continuous physiological data from wearables to personalize treatment and monitoring.
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