Related Experiment Video

Updated: Jun 14, 2025

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

11.8K

Shifting the paradigm in personalized cancer care through next-generation therapeutics and computational pathology

Jorge S Reis-Filho1, Maurizio Scaltriti2, Ansh Kapil3

  • 1Cancer Biomarker Development, Oncology Research and Development, AstraZeneca, Gaithersburg, MD, USA.

Molecular Oncology
|August 30, 2024
PubMed

Insights

Computational pathology enhances novel oncology therapeutics by enabling detailed biomarker analysis. This approach, integrating artificial intelligence, revolutionizes patient selection and drug development for advanced cancer treatments.

Area of Science:

  • Oncology
  • Biomarker Discovery
  • Computational Pathology
  • Artificial Intelligence in Medicine

Background:

  • Novel oncology therapeutics like antibody-drug conjugates and CAR T-cell therapies are shifting cancer treatment paradigms.
  • Accurate patient selection and response prediction require advanced biomarker assessment beyond traditional methods.
  • Key biomarkers include cell-surface target quantification, receptor internalization, and tumor microenvironment (TME) analysis.

Purpose of the Study:

  • To highlight the critical role of computational pathology in advancing novel therapeutic agents in oncology.
  • To demonstrate how computational pathology overcomes limitations of traditional biomarker assays.
  • To underscore the potential of artificial intelligence (AI) in revolutionizing biomarker discovery and drug development.

Main Methods:

  • Utilizing computational pathology for detailed assessment of target presence, expression levels, and intra-tumor distribution.
  • Analyzing phenotypic features of tumor cells and the surrounding tumor microenvironment (TME).
  • Integrating novel artificial intelligence (AI) models within computational pathology workflows.

Main Results:

  • Computational pathology enables comprehensive analysis of biomarkers essential for novel therapeutics.
  • This approach provides deeper insights into tumor biology and the TME compared to conventional techniques.
  • AI-driven computational pathology enhances the efficacy and specificity of advanced oncology treatments.

Conclusions:

  • Computational pathology is indispensable for the development and application of next-generation oncology therapeutics.
  • The integration of AI promises significant advancements in biomarker discovery and personalized medicine.
  • This technology is key to optimizing patient selection and predicting therapeutic response in cancer care.
Keywords:
antibody drug conjugatesartificial intelligencebiomarkerscomputational pathologydeep learningdigital pathology

More Related Videos

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors11:15

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Published on: September 20, 2016

24.3K
Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts10:27

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

Published on: July 25, 2020

7.2K

Related Concept Videos

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...
4.9K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
334
Cancer02:18

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
48.2K
Tumor Immunotherapy01:27

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
493
Cancer Vaccines01:30

Cancer Vaccines

Cancer treatment vaccines are a rapidly evolving field that offers a promising approach to immunotherapy. Unlike traditional vaccines that prevent diseases, cancer treatment vaccines are designed to treat existing cancers by stimulating the immune system to recognize and attack cancer cells.
Cancer vaccines come in two categories: preventive (prophylactic) and treatment (active). Preventive vaccines, such as the Human Papillomavirus (HPV) vaccine, protect against viruses that cause certain...
347
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
6.3K