The drugs and treatments we design are tested in large populations and prescribed using statistical averages. This vision of “one size fits all” determines that there is a variable group of patients who do not respond to treatment.

Currently, medical science is enthusiastically incorporating the knowledge that allows the success of treatment to be increased. The so-called Precision Medicine aims to identify the groups or subpopulations of patients that will have an optimal response to treatment. It seeks that the treatment considers, in addition to the variables commonly used today (age, weight, sex), genetic variability, lifestyle and the environment.

Precision Medicine then defines the disease and the response to the available pharmacological tools with a higher level of accuracy. Pharmacogenomics, also called pharmacogenetics, studies the response of genes to drugs and can explain why different responses to a drug or the appearance of undesirable effects in some patients and not in others.

Personalized Medicine has been the initial designation, now frequently replaced by Precision Medicine to avoid proposing the development of drugs for a single individual. The goal of Precision Medicine is to develop products that are effectively taking genetic factors into account.

Personalized medicine, because it is based on the unique genetic makeup of each patient, is beginning to overcome the limitations of traditional medicine. This allows professionals:

• Predict susceptibility to disease
• Improve disease detection
• Anticipate the progression of the disease
• Customize disease prevention strategies
• Prescribe more effective medications

Some of these new practices that contribute to the use of medicines and personalized treatments are:

3D Print

3D printing is a novel technology with great potential in the pharmaceutical field. It consists of manufacturing physical models using computer-aided design information, which the printer interprets and, thus, deposits the material layer by layer in the appropriate place.

3D printing could bring benefits to many patients. In the first place, for poly medicated patients, since a single drug can be created by combining different active ingredients

It could also have advantages for younger patients since many oral medications are not adapted for children. With this new technology, it would be possible to print smaller and easier-to-swallow tablets, in such a way that it facilitates the treatment.

It could also be useful for patients with rare diseases, who are less likely to access treatment due to the small population with the same disease. For more information, we invite you to read our article, 3D printing, the future of personalized medicine.

Big Data in Pharma

Big Data is a collection of data, structured or not, that can be explored (mined) to be used by processes such as automatic learning (machine learning), predictive modeling or other types of advanced analytical applications.

The use of new and powerful tools to explore Big Data sets has accelerated their use in the field of health (health care) and the pharmaceutical industry.

Different areas where big data is applied include drug and biomarker development, and basic cancer research, rare diseases, neurodegeneration, diabetes, and cardiovascular pathologies, among others.

Along with imaging, multi-omics data, and EHRs, patient-generated health data (PGHD), from wearable and implantable devices, is becoming an increasingly relevant type of big data in personalized medicine. For more information, we invite you to read our article, Big Data and Pharma.