Welcome to the Future: Personalized Medicine

Written by: Jamie Fernandez, B.Sc. in Genetics, Content Specialist

Peer-reviewed by: Edin Hamzić, Ph.D. in Genetics, Chief Science Officer

Medicine can be viewed as constantly evolving with discoveries and innovations continuously changing healthcare approaches. Innovations will always drive medicine forward, from vaccines to transplants to medical imaging. A prominent innovation in today’s medicine is personalized medicine. 

What is Personalized Medicine, and what does it mean?

Personalized medicine or precision medicine refers to a medical approach that tailors treatment and diagnostics to fit an individual or group of individuals. The importance of customizing medicine is to improve health care. For the most part, medicine has used a “one size fits all” approach; however, each individual is different in terms of genetic makeup and medical history. These differences result in some patients experiencing adverse drug reactions. Adverse drug reactions are a significant clinical problem that can result in hospitalizations and even death, thus negatively impacting patient well-being. Limiting the risk of adverse drug events is a primary concern in personalized medicine [1]. 

Genetic variations will determine an individual’s response to medication. Pharmacogenomic testing means doctors can now prescribe patients medication that maximizes efficiency and minimizes adverse drug reactions [2]. Pharmacoproteomics aims for drug discovery and development, whereas pharmacometabolomics considers metabolites that may interact with medications. Although ‘omic’-based approaches are beneficial for driving the field of personalized medicine, biomedical engineering and computational tools are also driving the field.

Integrating technology 

Wearable sensors refer to digital sensing devices patients can wear to monitor multiple aspects of their health. Wearable sensors can be used for general healthcare management. The latter entails the collection of large volumes of data in real-time that can be interpreted with algorithms. These algorithms automatically predict, prevent and intervene in such a way as to alter healthcare accessibility and patient quality of care [3]. 

Wearable devices include wrist-mounted devices that can sense activity, heart rate, blood pressure, and more, as skin patches that monitor body fluids for biomarkers in the form of electrolytes, proteins, and small molecules. The possibilities of wearable devices are growing, and most of them are associated with a mobile app for convent accessibility to the data. 

Additionally, ingestible pills that can monitor pH, temperature, heart rate, and blood pressure have also been invented [4]. These wearable devices form part of the concept of the Internet of Things, a global network that interconnects virtual and physical technologies collection and exchange of data [5]. However, with limitations such as a need for more cost-effective, accurate wearable devices, unstandardized system architectures, and multi-dimensional data generation, the Internet of Things has significant potential to revolutionize health care by driving personalized medicine [6]. 

What is the link between artificial intelligence and Personlaized Medicine?

The technical advances in personalized medicine can only be discussed with the mention of artificial intelligence (AI). AI has become an essential tool in personalized medicine to organize and interpret this data on a large scale. AI refers to the programming of machines to simulate human intelligence, enabling them to learn and problem-solve [7]. AI finds patterns in the ‘omics’ big data through algorithms based on machine learning, neural network constructs, and deep learning. Through this, AI has an important role in personalized medicine as it can be applied to diagnostics, predicting prognosis, and identifying optimal treatment plans [8]. 

Furthermore, the digital approach to personalized medicine has incredible implications for future developments. One such development is DigitalMe™, a concept that uses data from an individual to generate a virtual avatar. The data required for this is based on a multi-omics approach using wearable sensors, family and medical history, and lived experiences. The DigitalMe™ avatar can act as a test dummy for patients to try out treatments and simulate a potential response to the treatment without any unnecessary or inconvenient risk to themselves. Moreover, the outcomes from testing treatments on these virtual patients can be shared on a social networking platform called PatientsLikeMe to add to the data used in personalized medicine [9]. 

The technological advancements in personalized medicine can be seen in cardiovascular medicine. Heart failure can affect roughly 1-2% of the population in wealthier countries, and the type of arrhythmia known as atrial fibrillation is commonly associated with heart failure. Currently in development is a patch with an electrocardiogram monitor, radiofrequency sensor, and transmitter that measures pulmonary fluid content that has the potential to predict heart failure decompensation (a syndrome caused by a structural or functional change in the heart leading to its inability to maintain physiological pressure levels) [10]. Additionally, significant strides forward in cardiovascular health care have been made using machine-based learning in AI. AI has provided an opportunity for cardiovascular research to focus on complexities and diversities in these diseases as it removes the limitations of simple, traditional statistical tools when analyzing big data. This has further implications in personalized medicine as AI facilitates a greater standard of health care by assisting physicians in making decisions regarding the diagnosis, treatment, and predicting the outcome of patients with cardiovascular disease [11].

Medical treatment should not be a one-size-fits-all approach. Personalized medicine has pushed the medical industry to optimize patient health. Despite the vast amount of research available for personalized medicine, many more studies and clinical trials will have to be undertaken before healthcare systems entirely rely on personalized medicine. Although there are many limitations to the advancement in personalized medicine, such as cost, research aimed at improving quality of life inspires hope for the future.

*Disclaimer: The term “drug” in the above article refers to a chemical substance used to treat, cure, diagnose or prevent a disease or condition. Alternatives for this term include medication, pharmaceutical or therapeutic agent. In this context, “drug” does not refer to any type of illegal stimulant or recreational drug.

References 

[1] C. Y. Wei, M. T. Michael lee, and Y. T. Chen, “Pharmacogenomics of adverse drug reactions: Implementing personalized medicine,” Hum. Mol. Genet., vol. 21, no. R1, Oct. 2012.

[2] D. B. Singh, “The Impact of Pharmacogenomics in Personalized Medicine,” in Advances in Biochemical Engineering/Biotechnology, vol. 171, Springer, 2020, pp. 369–394.

[3] J. Dunn, R. Runge, and M. Snyder, “Wearables and the medical revolution,” Personalized Medicine, vol. 15, no. 5. Future Medicine Ltd., pp. 429–448, 01-Sep-2018.

[4] K. Guk et al., “Evolution of wearable devices with real-time disease monitoring for personalized healthcare,” Nanomaterials, vol. 9, no. 6. MDPI AG, 01-Jun-2019.

[5] D. R. Kiran, “Internet of Things,” in Production Planning and Control, Elsevier, 2019, pp. 495–513.

[6] J. Qi, P. Yang, G. Min, O. Amft, F. Dong, and L. Xu, “Advanced internet of things for personalised healthcare systems: A survey,” Pervasive and Mobile Computing, vol. 41. Elsevier B.V., pp. 132–149, 01-Oct-2017.

[7] J. Frankenfield, “Artificial Intelligence (AI) Definition,” 2021. [Online]. Available: https://www.investopedia.com/terms/a/artificial-intelligence-ai.asp. [Accessed: 07-Apr-2021].

[8] N. J. Schork, “Artificial Intelligence and Personalized Medicine,” in Cancer Treatment and Research, vol. 178, Springer International Publishing, 2019, pp. 265–283.

[9] S. Okun and P. Wicks, “DigitalMe: A journey towards personalized health and thriving,” BioMedical Engineering Online, vol. 17, no. 1. BioMed Central Ltd., p. 119, 06-Sep-2018.

[10] A. Singhal and M. R. Cowie, “The Role of Wearables in Heart Failure,” Current Heart Failure Reports, vol. 17, no. 4. Springer, pp. 125–132, 01-Aug-2020.

[11] C. Krittanawong, H. J. Zhang, Z. Wang, M. Aydar, and T. Kitai, “Artificial Intelligence in Precision Cardiovascular Medicine,” Journal of the American College of Cardiology, vol. 69, no. 21. Elsevier USA, pp. 2657–2664, 30-May-2017.

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