Multi-Gene Precision Panel for Obesity Medication Selection
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Solution Overview
Problem
Current obesity treatment relies heavily on trial-and-error prescribing without genetic screening, leading to suboptimal outcomes and avoidable side effects due to variable patient responses to anti-obesity medications.
Innovation Solution
A multi-gene panel and companion diagnostic kit that predicts medication efficacy and safety by analyzing 16 key genetic markers, including GLP-1 R, CNR1, TCF7L2, SLC47A1, and others, to tailor pharmacotherapy to individual patient biology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trial-and-error prescribing is used without genetic screening, then treatment coverage is achieved, but treatment efficacy is suboptimal and side effects are avoidable
Solution Approach 1:
The patent performs genetic screening before initiating anti-obesity medication treatment to predict patient response in advance. By analyzing genetic variants associated with drug metabolism and response (such as CYP2C9, CYP2C19, CYP3A4, CYP3A5, CYP2D6, SLCO1B1, and other genes related to GLP-1, insulin, and appetite regulation), the system identifies the most effective medication regimen before treatment begins, eliminating the need for trial-and-error prescribing and reducing the time to achieve effective treatment.
2Adaptability or versatility
If standard pharmacological treatments are applied uniformly, then treatment accessibility is maintained, but individual patient responses vary greatly
Solution Approach 1:
The patent applies local quality by tailoring the treatment approach to each patient's specific genetic profile. Instead of uniform treatment, the system analyzes individual genetic variants (such as CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2D6*4, SLCO1B1 c.521T>C, and other polymorphisms) to determine the most appropriate medication and dosage for each patient, making the treatment adaptive to individual biological characteristics while managing complexity through automated genetic analysis algorithms.
3Measurement precision
If genetic screening is implemented, then treatment precision is improved, but testing and analysis requirements increase
Solution Approach 1:
The patent employs a multi-functional genetic testing system that simultaneously analyzes multiple genes and variants related to drug metabolism (CYP2C9, CYP2C19, CYP3A4, CYP3A5, CYP2D6, SLCO1B1), hormone regulation (GLP-1, insulin pathways), and appetite control. This universal testing approach achieves high prediction accuracy for drug response while consolidating multiple analysis functions into a single comprehensive genetic screening platform, reducing the overall complexity of implementation.
Data Source
AI summary
The present invention provides a method for precision anti-obesity therapy, utilizing a proprietary panel of genetic variants to predict individual patient response to weight-loss medications as well as a related companion diagnostic. In particular, the method analyzes variants in genes including GLP-1 R, CNR1, TCF7L2, DPP4 and others, which have established associations with drug efficacy and metabolism in obesity treatment. By genotyping these markers, the method guides selection and dose optimization of specific anti-obesity medications—such as GLP-1 receptor agonists, metformin, SGLT2 inhibitors, and DPP4 inhibitors—tailored to the patient's genetic profile. Notably, GLP-1R polymorphisms (e.g., rs6923761) are leveraged as especially predictive indicators of enhanced weight loss response to GLP-1 receptor agonists. Through this innovative genetic profiling approach, the invention enables personalized treatment strategies that maximize efficacy, minimize trial-and-error in drug choice, and reduce adverse effects, thereby embodying the principles of precision medicine in obesity care.