The increased relevance of pharmacogenomics in explaining individual differences in drug responses is evident in the market’s projected growth to $9,346.8 million by 2031. The CRISPR Cas-9 gene editing, computer assisted structural simulation and DNA reactivity technology provide key insights for informed trial design, especially in Oncology studies where both germ line and acquired mutations play a role.
The complete human genome was published in March 2022, heralding a new era in pharmacogenomics, advancing genome analysis, and unlocking value additions in precision medicine. It received a considerable impetus in the global market when former US President, Barrack Obama, announced the Precision Medicine Initiative in 2015. According to a McKinsey report, the precision medicine market is set to touch US$ 140 billion by 2026, with the growing demand bringing to the fore the need to conduct pharmacogenomics studies, adding new dimensions to clinical trials.
Variations in genes that code for specific enzymes, drug targets, or even transporters have been shown to be associated with drug toxicity and may be used for identifying likely responses to drug products. An understanding of such variations that are present from birth, or germline variations, are inherited and are used as biomarkers to understand the pharmacokinetics of drugs. The increased relevance of pharmacogenomics in explaining individual differences in drug responses is evident in the market’s projected growth from nearly US$ 5,000 million in 2020 to US$ 9,346.8 million by 2031 at a CAGR of 5.71 per cent.
There are inter-individual differences in the response to drugs that are multifactorial and difficult to predict, but are partly associated with inherited genetic variations. Variations in genes associated with absorption, distribution, metabolism, and excretion (ADME) have been found to be associated with a drug’s pharmacokinetics (PKs) and pharmacodynamics (PDs), affecting various aspects of drug outcome. Gene variations are also associated with drug dosing, toxicity, the extent of effect, and even drug resistance and hypersensitivity.
The genetic testing and genomic services ecosystem is rapidly evolving, with the main drivers being advances in technology, improved utilisation of genetic information, and better delivery of information. Tiered single-gene methods and multigene panels have given way to genome-wide sequencing, and genome or exome sequencing, increasing the potential for faster genetic testing services.
Such advances have improved the clinical use of genetic information, or pharmacogenomics, for the past 15 years. This wide-ranging field of study utilises the information present in DNA variants to identify people who may be hypersensitive to certain drugs.
Germline variations that are known to affect the pharmacodynamics and pharmacokinetics of a drug are estimated to explain 20-40 per cent of the variation in drug response. In order to study the effect and the likely therapy, however, the conduct of randomised clinical trials is a little more complicated when it is a pharmacogenomic study.
Pharmacogenetic trials that are prospective compare a standard arm with a pharmacogenetic guided arm. Such studies are generally singleblinded, and the study participant is unaware of the arm that they are a part of. However, the clinical investigator is aware, and there are certain challenges in implementing medications. For example, there are multiple clinical genotyping panels that are available to support the prescription of antidepressants, however, only five pharmacogenetic trials for antidepressants were randomised, all the others were single-blinded studies.
Another aspect of prospective pharmacogenetic trials is that there is a need for a large sample size, as the effect of the gene variants may be modest, so there may be difficulties encountered in patient recruitment for the study.
Certain other factors that could affect such trials include the absence of ethnic diversity, clinical and environmental confounders as well as logistical considerations like the delivery of therapeutics, the tracking of adverse events manually, and compliance from patients. Such issues may be overcome by the incorporation of recent innovations that could shape the conduct of pharmacogenomic clinical trials.
The use of digital devices has been shown to significantly improve the conduct of pharmacogenomic clinical trials. The use of wearable devices is already common in many clinical trials, where user activity is tracked by the device to capture digital biomarkers and associated outcomes like walking, sleeping, or even collecting electrocardiograms. In psychiatry pharmacogenomic studies, episodes of anxiety have been monitored using such wearable devices.
Other interesting devices that have been used in pharmacogenomic trials include a device to measure blood pressure as well as anticoagulation levels for pharmacogenetic trials focused on cardiac therapy. There are specially designed apps that can be used on smartwatches like SmokeBeat, which detects how many times an individual carries out hand-tomouth gestures. An effective app that can be used to understand the association of gene variants with smoking cessation.
A significant step forward in pharmacogenomics is the use of clustered regularly interspaced short palindromic repeats (CRISPR) based gene editing that allows pharmacogenomic screening of lab-grown cells in different flasks. Such innovative strategies allow scientists to identify genomic changes that influence the clinical effects of a drug.
The information can then be used to check clinical trial participants for the presence of certain gene variations associated with altering the activity of certain drugs. This will help in improving the trial design, improving safety and efficacy, and providing specific solutions. This technology is currently being used in cancer research, but with improvements in technology, it can be used to provide insights into other medical conditions as well.
Pharmacogenomic biomarkers have provided a lot of tangible and intangible benefits. The tangible benefits have been the discovery of new COVID-19 medications while the intangible benefits have been the strategic insights gained that have helped broaden the understanding of the fight against COVID-19.
One of the many genetic variants associated with varied response to COVID-19 is the ACE2 gene variant. Angiotensin-converting enzyme 2 (ACE2) has been shown to be the receptor for entry of the SARS-CoV-2 Coronavirus. The ACE2 enzyme leads to the degradation of the angiotensin II, which facilitates the entry of the virus. Recent studies have shown a possible association between ACE gene variants and severity of COVID-19 outcomes, highlighting a likely genetic contribution.
As a result, pharmacogenomics is expected to provide key insights into therapeutic innovation for COVID-19, especially as new COVID-19 waves are expected. Such insights will help immensely in contributing toward drug discovery, as well as being a decisive factor in the design of clinical studies.
A new and emerging field of phenomics 2.0 shows promise, aiding in real-time drug-related outcomes for association analysis based on pharmacogenomics. Phenomics is expected to provide a deeper understanding of phenotypes by capturing the living architecture of disease progression with digital dynamics.
The concept of the Internet of Pharmaceutical Things (IoPT) aligns experience innovation with process innovation to ascertain a wide range of phenotypes specific for innovative COVID-19 medicines. There are potential applications of this innovative system in pharmacy services, for comprehensive drug response to COVID-19.
There are a number of preventive and therapeutic applications that can be developed for clinical, pharmacy, and health practices using pharmacogenomics. Pharma companies have, for a long time, depended on a manual workforce and siloed environments, however, successful partnerships have aided in innovations that greatly support the growth of the industry.
A global pharmaceutical company partnered with a major software company to develop a tech-enabled house called ‘Parkinson’s House’. Multiple sensors are placed in the house to analyse and monitor the movements of patients to aid in supporting their condition, revolutionising both support and care. In another instance, a global clinical research organisation utilises OneClinical to reduce the time in mapping highly complex studies by up to 50 per cent, coupled with a 60 per cent improvement in cycle time to develop an initial Interface for the data warehouse, and a 30 per cent cost reduction.
Precision medicine in oncology saw progress with the OncologyCloud platform that has been designed to combine Electronic-Medical-Record (EMR), claims billing, longitudinal clinical data, as well as analytics for nearly two million patients with active cancer. This helps support targeted therapy, for example, for individuals with epidermal-growthfactor-receptor (EGFR) and the anaplastic- lymphoma-kinase (ALK) mutations.
Such innovations will help in speeding the development of tailor-made therapies, while adhering to all data privacy regulations. There is an increased pace of innovation in utilising the EMR, with multiple stakeholders supporting personalised medicine by actively linking EMR with genomic medicine. To safeguard data, there are stringent regulations like the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States.
Advanced analytics are leveraged for the development of highly precise drug therapy, especially for rare diseases. Such technology solutions aid the gathering of data from multiple sources, translating the information into easily assimilable insights that companies use to understand individual behaviour.
Real world evidence (RWE) is being employed in innovative ways using the analytics capabilities that are available. RWE has been used extensively to understand patient behavior but is now being leveraged to help move precision medicine from a detailed understanding to enabling predictive approaches.
Effective use of RWE in oncology clinical trials is in the synthetic control arms. Such arms aid in overcoming challenges posed in patient recruitment in randomized clinical trials, as well as in combating ethical issues faced when supporting placebo arms.
Regulatory authorities also favor RWE, with approval provided in certain instances. For example, the information provided by RWE was utilized to expand the label for IBRANCE, a prescription medicine, to include male breast cancer by the US Food and Drug Administration (FDA) in 2019. The drug is used as a treatment for breast cancer patients who test negative for human epidermal growth factor receptor 2 (HER2) and positive for hormone receptors. This cancer is extremely rare among men, and such RWE-based approvals will aid in the ability to bring life-saving medicines to people who most need them quickly.
In conclusion, Pharmacogenomics is undoubtedly poised for greater acceptance and relevance with pragmatic clinical trial design required to tap into advancements in DNA technology and digital health solutions to harness the big data from genomics. This will help revolutionise care and provide highly targeted medical therapy. Supported by efficient clinical trials, pharmacogenomics will help in shaping the future of medicine.