AI in Therapeutics and Decision Support

AI in Therapeutics and Decision Support

Introduction

AI is not limited to diagnostics—it also guides treatment choices and supports decision-making at the bedside. From precision dosing and sepsis management to robotic surgery, AI-enabled tools are shaping how therapies are delivered. This post examines therapeutic applications of AI and highlights the critical importance of keeping clinicians in the loop.

Precision Dosing

Dosing is highly variable across patients due to genetics, comorbidities, and drug interactions. AI-driven models can personalize therapy by integrating pharmacogenomic data and real-world patient factors. Examples include:

  • Warfarin dosing calculators using ML algorithms.
  • Oncology regimens tailored to tumor genomics and patient profiles.
  • Adaptive insulin delivery systems (closed-loop “artificial pancreas”).

Clinical Decision Support

AI enhances decision support systems (CDSS) embedded in EHRs. Key use cases include:

  • Sepsis early-warning systems prompting timely antibiotics.
  • Risk scores suggesting ICU admission or escalation of care.
  • Drug–drug interaction alerts refined by AI to reduce alert fatigue.

Robotic and Surgical Assistance

In surgery, AI augments robotic platforms by providing:

  • Automated recognition of anatomical landmarks.
  • Real-time alerts for potential complications.
  • Assistance in precision movements guided by image analysis.

AI Decision-Support Loop

A therapeutic AI system typically follows a loop: input data → model analysis → recommendation → clinician oversight → action. This ensures AI enhances, but does not replace, medical judgment.

Patient Data AI Model Analysis Recommendation Clinician Oversight Action + Feedback

Limitations and Risks

  • Over-reliance: risk of deskilling if clinicians follow recommendations uncritically.
  • Alert fatigue: excessive prompts may be ignored.
  • Liability: unclear responsibility when AI recommendations contribute to adverse outcomes.

Conclusion & Next Step

AI in therapeutics is already assisting in dosing, monitoring, and surgical care. The future promises more personalized, dynamic treatment support—but human oversight remains critical. In the next level, we transition to Advanced Topics: Bias, Fairness, and Explainability.