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Related Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase01:11

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...

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Related Experiment Video

Updated: Jun 7, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

Optimizing genomics-aware clinical agents in precision oncology.

Rangan Das1,2, K Maheswari1, Shaheen Siddiqui1

  • 1GeneSilico Inc., Austin, Texas, USA.

NPJ Systems Biology and Applications
|June 5, 2026
PubMed
Summary

Workflow orchestration with curated tools enhances safety and reliability in AI-driven oncology decision support. Constrained agentic systems, not broad tool access, improve guideline concordance and patient-specific recommendations.

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Related Experiment Videos

Last Updated: Jun 7, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

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Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

Published on: July 25, 2020

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

  • Artificial Intelligence in Medicine
  • Clinical Decision Support Systems
  • Precision Oncology

Background:

  • Agentic systems offer potential for clinical decision support.
  • Unrestricted tool access in AI can compromise safety and accountability in precision oncology.
  • Oncology recommendations require adherence to guidelines, labels, and patient molecular data.

Purpose of the Study:

  • To compare the safety and reliability of different agent architectures for oncology decision support.
  • To evaluate the impact of tool access breadth versus workflow orchestration on AI performance.
  • To determine the optimal approach for grounding AI recommendations in clinical evidence.

Main Methods:

  • Compared four agent architectures: standalone LLM, unconstrained function-calling, ReAct, and workflow-orchestrated (gSage).
  • Evaluated 375 clinician questions across 41 cancer cases using multiple LLM backbones.
  • Employed LLM rubric scoring, expert adjudication, and embedding-based content concordance analysis.

Main Results:

  • The workflow-orchestrated agent (gSage) significantly outperformed other architectures.
  • gSage achieved superior performance on guideline concordance, correctness, patient centricity, transparency, and safety.
  • gSage demonstrated the highest embedding recall using both biomedical and general-purpose models.

Conclusions:

  • Principled workflow orchestration with constrained, curated tools is crucial for reliable and safe genomics-aware oncology decision support.
  • Maximal tool breadth does not guarantee improved performance or safety.
  • Constrained, orchestrated agentic systems enhance accountability and evidence-based recommendations in precision oncology.