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Personalized & Precision Medicine in Drug Development

The importance of individual patients has long been recognized by the medical industry. There is an old saying that helps highlight the concept of personalized medicine, which is: “physicians must understand what person the disease has, rather than what disease the person has.” However, until fairly recently a “one size fits all” approach aimed at treating the “average” patient (with subtle variations), versus treating the individual, was often the only available option for physicians.

Personalized or “precision” medicine is about providing a more tailored treatment for patients, one that precisely targets attributes that are unique to an individual. The completion of the human genome project in 2003 established the role of pharmacogenomics in personalized medicine and has had a significant impact on how drugs are developed and how patients are treated.

A deeper understanding of pharmacogenomics coupled with rapid technological development in proteomics and improved data processing has enabled personalized and precision medicine to take off over the last two decades.

What is Personalized Medicine?

Personalized medicine uses information from an individual’s own genes or proteins and takes intrinsic factors, such as body size, ethnicity, and gender, into consideration to prevent, diagnose, or treat diseases.

By looking at the genetic profile of an individual, personalized medicine provides insight into the risk of specific diseases’ onset and types of medication that will work best and with the least amount of side effects for that individual. This helps determine which patients should get certain kinds of treatments, specific doses of a given therapy, or who should be monitored more carefully given they are predisposed to a particular safety concern.

Fast, large scale, and low-cost DNA sequencing is at the center of delivering the next generation of personalized medicines using pharmacogenomic profiling. The number of drugs with labeling information recommending dose and dosing regimen changes based upon pharmacogenomic biomarkers is rapidly increasing to support a more personalized medicine approach.

While pharmacogenomic information is being used to personalize treatments for a variety of conditions (like cardiovascular diseases, HIV, and cystic fibrosis), this shift has been particularly evident in treatments for cancer wherein both the genome of the patient (germline) and the genome of the cancerous cells is mapped to arrive at a specific treatment plan.

Importance of Personalized Medicine

The current shift towards personalized and precision medicine is necessary due to the complexity and variability of diseases like cancer, cystic fibrosis, and Alzheimer’s, to name a few. On average, only 25-35% of patients suffering from these types of diseases respond to drugs that are currently available, resulting in poor prognosis. This also means that for a significant proportion of patients, the medication prescribed is not the right solution for those individuals, and if such is available, an alternative treatment is needed.

Furthermore, the time course for a disease’s inception, progression, and prognosis of the correct treatment modality can be dramatically different depending upon the genetic makeup of individual patients. For example, many diseases, including some types of cancers, are caused by genetic alterations of an individual’s cells and progress at different paces. Similarly, some patients may be susceptible to certain side effects, ranging from minor discomfort to serious harm, due to their genetic predisposition. An example of this can be found in Asian populations where an intolerance to thiopurines can lead to life threatening myelosuppression.

Benefits of Personalized Medicine

The applications and uses of personalized medicine are vast wherein genetic information of an individual can be used in the prevention, detection, and treatment of diseases. Some examples of how precision medicine can greatly improve treatment outcomes include the following advantages:

  • Allows for preventive and definitive therapeutic approaches
  • Minimizes adverse drug reactions
  • Allows dose and dosing frequency adjustments

Pharmacogenomic information can be used to predict the susceptibility of an individual to certain diseases so that adequate steps (such as lifestyle changes or preventive medicine) can be taken to minimize the risks associated with those diseases. For instance, a single nucleotide polymorphism within the TCF7L2 gene is the most significant genetic biomarker linked to a higher risk of developing Type 2 diabetes. Individuals with this polymorphism can proactively start changing their lifestyle to minimize their risk of developing Type 2 diabetes.

From a treatment standpoint, personalized medicine allows physicians to choose a drug or treatment that minimizes the amount of side effects and produces adequate efficacy in each individual patient. Personalized medicine also associates specific genetic polymorphisms with safety and efficacy outcomes in patients. For example, in cancer treatments, genetic profiles of tumors and their microenvironments have been used as a predictive tool to maximize efficacy and improve prognosis.

Clinical Trials for Precision Medicine

Randomized clinical trials (RCTs) have long been used to establish the relationship between interventions and outcomes in drug development. However, the emergence of precision medicine has reduced the importance and application of large population-based RCTs for interventions that are specific for individual patients based upon genetic and biochemical profiles.

Precision medicine clinical trials are markedly different from traditional trials due to the focus on individual responses as opposed to the average response. In such cases, clinical studies can enroll a smaller number of patients with a consistent genetic and biochemical profile, or even a single patient (N-of-1 trial), to sufficiently establish the safety and efficacy of personalized interventions.

Since precision medicine is helpful to a subset of patients with a specific genetic make-up, the following factors need to be accounted for while designing a precision medicine clinical trial:

  • There is a limited number of patients who may have the genetic profile required for recruitment in the trial
  • There may be additional logistic and financial difficulties in screening patients for inclusion in the study based upon their genetic profile that is not typically encountered in traditional RCTs
  • There may be additional ethical issues when conducting a comparative trial wherein the comparator is most likely inferior to the personalized medicine being tested

N-of-1 trials are designed to assess the effects of an intervention based on an individual patient. The study usually follows multiple cross over designs wherein the intervention and comparator/placebo are given alternately to the same patient after a suitable wash out period. The use of appropriate controls and integrating blinding into the study design is important to consider since responders and non-responders can often be easily identified for each intervention. The combined results of different N-of-1 studies can be collated to offer insights into the best way of treating a subset of patients being studied.

Basket and umbrella trial designs have been developed to account for inter-subject variability in precision medicine clinical trials. In basket trial designs, volunteers are placed into baskets based upon the genetic profile of their tumor irrespective of the tumor site. Patients in each basket are matched to an intervention based upon the genetic profiles of their tumors. In umbrella trial designs, multiple drugs are given for the treatment of a single disease. Based upon the responses obtained during the umbrella design, the genetic make-up of patients’ tumors can be associated with the efficacy of one or more of the drugs used in the trial.

How Modeling & Simulation Can Improve Personalized Medicine

Model informed drug development (MIDD) is widely accepted by regulatory agencies and can significantly reduce the cost and duration of precision medicine clinical trials. Two types of modeling approaches known as quantitative systems pharmacology (QSP) and physiologically based pharmacokinetic (PBPK) modeling have both been used for personalized medicine drug development.

QSP can address genetic variability to predict pharmacodynamics (PD) and clinical efficacy outcomes in individuals. PBPK modeling can help predict the pharmacokinetics (PK) of drugs in humans and evaluate the effect of intrinsic (genetics, organ dysfunction, or age) and extrinsic (drug-drug interactions) factors on drug exposure.

In one example, a PBPK model created from data based on a drug’s and its metabolites’ effects on a population of European ancestry was then used to predict the PK of a drug in a Japanese population with a poor metabolizing phenotype of CYP2C19.

Conclusions

Personalized medicine has resulted in a paradigm shift in many drug development programs by allowing the deliberate enrollment of patients who will benefit the most from various experimental interventions.

The concepts of personalized medicine have existed in healthcare for a very long time. However, technological advances and improved data processing in the last few decades have resulted in a deeper understanding of pharmacogenomics which has helped drug developers and physicians implement personalized medicine concepts into the clinic and into real-world treatments. Additionally, advances in DNA sequencing with respect to speed and cost have also played an important role in access to personalized medications with better efficacy and fewer side effects.

Nuventra has an expert team of clinical pharmacologists to help design your precision medicine clinical trial. Contact us to learn more about our services and how we can help you gain insights that move your program forward.

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