Personalised (precision) medicine: what is it, and how does it work?

John received chemotherapy for colon cancer. The chemotherapy drug that he used, however, was not effective for him. He also experienced severe nausea and diarrhoea when using this chemotherapy.

He speaks to another patient treated at the same hospital, who has the same type of colon cancer and who received the same chemotherapy. For this patient, the chemotherapy was very effective and the patient only experienced mild nausea. What causes these differences between patients and what approaches are needed to overcome them?

Patients have different responses to different treatments, as well as different adverse reactions[1]. These differences could be caused by genetic or other factors. The solution here lies in personalised, or precision, medicine.

What is personalised medicine?

Personalised medicine is the concept of adapting patient treatment (drug and dosage) to a specific patient, based on that patient’s specific characteristics, such as genomic information and environment[1].

The aim of personalised medicine is to provide a patient with the correct treatment regimen that will potentially result in better treatment of a disease, as all patients do not have the same characteristics and do not respond the same to the same treatment.

What is required for personalised medicine to work?

Personalised medicine typically consists of two parts: firstly, using diagnostic medical devices to identify specific characteristics of a patient. Diagnostic devices or tests could include, amongst others, genetic tests, or imaging equipment. Secondly, therapeutic products (drugs, devices or other treatments) are provided based on the results of the diagnostic test[1].

This implies that there could be a synergy or collaboration between device and pharmaceutical companies in providing personalised medicine to a patient.

For personalised medicine to be successful, data on past patients should be available. This can be in the form of patient registries or clinical trials. This data should include the various characteristics of the patients (for instance, biomarkers, genetic information, age, gender, family history, etc.) and disease (especially if the disease can present in different ways). This data should also provide information on the outcomes for patients using specific drugs.

Predictive and prescriptive modelling can be used to analyse this data and provide insights into the relationships between patient characteristics (biomarkers, genetic information, etc.) and the outcome (cure or survival using a specific drug). Predictive and prescriptive modelling can also be used to determine if patient characteristics have a significant impact on the outcome, whereas this can become a focus point or objective for further research. This is done to further improve knowledge and treatment habits for a given patient.

As mentioned in a previous blog post, “Predictive and prescriptive modelling in health care”, TCD Outcomes Research can assist you in your prescriptive and predictive modelling requirements. We can also assist in positioning your product, using this information, for the correct market segment. This will not only assist the pharmaceutical or medical device company, but also the patient, for whom funding for the correct treatment would more likely be available from the medical aid. A patient would also know that treatment with a specific drug is catered to their needs and that the patient receives the best treatment based on his/her medical records.



  1. S. Food and Drug Administration. Paving the Way for Personalized Medicine – FDA’s Role in a New Era of Medical Product Development. October 2013. Available from: Accessed on: 15 March 2017.

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