What is precision medicine?

According to the Precision Medicine Initiative at the U.S. National Institutes of Health, precision medicine is defined as, “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.”

This approach enables doctors and researchers to predict, with greater accuracy, which treatment and prevention strategies for a particular disease will work in which groups of people. Precision medicine contrasts with a one-size-fits-all medical approach, in which disease treatment and prevention strategies are generated for the average person in a given population, with little consideration to individual differences.

What is pharmacogenomics?

Pharmacogenomics is the study of how genes affect a person’s response to particular drugs and is a key part of precision medicine. This relatively new field combines pharmacology (the science of drugs) and genomics (the study of genes and their functions) to develop effective, safe medications and doses that are tailored to variations in a person’s genes.

What is precision oncology or precision cancer medicine?

The terms precision oncology and precision cancer medicine can be used interchangeably. Precision oncology involves identifying the best possible treatment and prevention strategies for individual patients and using and sharing this knowledge to advance precision oncology research for the population at large. The capacity to start the right treatment at the right time for the right duration can save patients from unnecessary treatments, as well as ensure that an optimal sequence of treatments is being employed from the outset. Researchers use patients’ unique molecular data, combined with their clinical data and environment, to achieve precision cancer medicine.

How does Olympus support precision medicine?

Olympus provides a range of tools to assist in precision oncology, including the following:

• Endoscopes for surgical biopsy
• Histology microscopes
• Automated whole slide imaging microscopes
• 3D confocal scanning microscopes
• 3D analysis software
• AI-powered deep-learning technology

3D and AI imaging and analysis solutions

Using 3D images acquired by our scanning systems, Olympus’ 3D analysis software can provide statistical information about tumor spheroids and organoids. Our deep-learning technology enables researchers to train the scanning system’s neural network to perform rapid label-free object identification and classification.

The Ellison Institute, for example, uses Olympus’ FV3000 microscope and cellSens software’s TruAI deep-learning module for automated high-speed drug screening. They also configured an automated high-content screening system with the FV3000 microscope, exploiting our software’s macro-micro scanning function for 3D organoid detection and targeted imaging.

Tumor localization and primary diagnosis

Minimally invasive, multimodal endoscopes enable physicians to precisely locate the tumor and collect samples for biopsy with minimal disruption of surrounding tissue.

Histology and 3D/4D cellular and molecular characterization

In traditional histology, the biopsied tissue is stained, enabling a trained pathologist to examine it using a microscope or for the tissue to be scanned by a whole slide imaging microscope.

New 3D/4D cellular and molecular characterization methods are providing physician-scientists with more information, including the capacity to compare changes in live-cell imaging over time—the 4th dimension.

Live tumor tissue is biopsied from the patient in the clinic and transported to the research lab, where the tumor tissue is dissected into single cells and placed in a series of mini-well microplates, where they grow into spheroids. Because each microwell is self-contained, researchers can test different compounds to determine which combination might be the most effective weapon in fighting an individual patient's tumor.

Scientists can also capture high-resolution 3D/4D images of the organoids to obtain critical information about the individual patient’s tumor, including the number and type of cells, morphology, cell growth or death rates, and then ultimately, use this information to help monitor the effectiveness of the latest anti-cancer compounds.