Personalised and precision medicine is often touted as the future of modern healthcare. With revolutions in genotyping technology, we have the ability to rapidly and affordably look into the majority of the whole genome for almost any patient. What better proof of progress in whole human genome screening than Genomics England’s vision and plan to create the most advanced genomic healthcare system by recruiting up to 5 million diverse participants, following their successful completion of the 100,000 Genome Project - the largest study of its kind worldwide.
However, the evidence and tools that support what to clinically do with all of that information are severely lagging behind, particularly in the applications towards female reproductive health. It’s time we utilise some of science’s greatest tools to make healthcare more inclusive for those whose needs have largely been neglected in the past. We believe that the future of personalised and precision medicine for female reproductive health starts with contraception!
But what does personalised medicine actually mean? How can we know if a healthcare treatment truly offers personalisation or whether it’s just another commercial buzzword? And how far are we from truly achieving this?
Personalised and precision medicine - what does it mean?
Before we get to the crux of the problem, let’s talk about personalised medicine, and what these mean exactly:
The right drug, with the right dose at the right time to the right patient.
Personalised medicine has the potential to transform medical interventions by looking at an individual and their unique physiological characteristics, and tailoring medical interventions accordingly. The term is often used vaguely, however, a systematic review that looked into 2457 articles containing the term ‘personalised medicine’ draws the following definition:
The tailoring and timing of preventive and therapeutic measures by utilizing biological information and biomarkers on the level of molecular disease pathways, genetics, proteomics as well as metabolomics.
Personalised medicine is rooted in the idea that unique and nuanced molecular, physiological, environmental and behavioural factors, have an impact on how an individual may respond to a particular medical intervention. A truly personalised approach aims to take into account all potentially impactful factors. A combination of such factors could enable us to predict which medical treatments are the safest and most effective for each patient. The current alternative is looking at averages or population results from clinical trials which do not always fit the individual.
Personalised and precision medicine is commonly used interchangeably. In precision medicine, novel therapeutic models are based on the understanding of the interrelation between environment, lifestyle, and genetic factors, which enables choices of a specific drug type, dosage and predictions of responses as well as new drug developments. Precision allows physicians to choose the right treatment and the best timing of administration, consequently maximising drug efficacy, and, possibly, reducing adverse events.
The terms personalised medicine, stratified medicine and precision medicine are also close relatives of pharmacogenetics, another important concept worth defining in this article. The study of pharmacogenetics is showing why there are varieties in responses to medications between individuals and oftentimes used to predict the efficacy of treatment. Interestingly, research has shown that polymorphisms of drug-metabolising enzymes, transporters and receptors all contribute to variable drug responses.
Applications of personalised medicine
There have been vast advancements in the field of personalised medicine and many examples where molecular and cellular markers tailor treatments for patients, such as in the fields of oncology, immunology, genetic conditions.
For example, some patients with breast cancer are resistant to Herceptin, which is an extremely useful drug for around 20–30% of breast cancer patients with elevated HER2 gene. Molecular characterisation of breast cancer patients at both a genetic and epigenetic level allows for the optimal use of Herceptin. Another example is the tailored approach to cystic fibrosis management. The dose of supplementary digestive enzymes is adjusted, not only based on the patient's physiological characteristics, but also considering the response to the enzyme, volume of food ingested, type of food ingested, number of meals, body mass gain, growth rate, and the type of enzyme used.
Pharmacogenetics is also increasingly being adopted in clinical settings. For example, patients who suffered a myocardial infarction, need antiplatelet therapy, most commonly a drug called clopidogrel. It’s been found that some patients have a certain genetic variation (CYPC19) which means that they cannot metabolise clopidogrel in its active form, increasing the risk for recurrent myocardial infarction. For this reason, such patients will require a different prescription than the current first-line clopidogrel.
Contraception & Dama Health
How can all of this apply to contraception? Well, whenever there’s a long range of factors to consider and a long list of possible therapies, personalised medicine can help. And that’s exactly the case with birth control.
When prescribing contraception, doctors need to consider medical factors, risk factors, past experience and preferences to choose a suitable one all in a limited appointment time. On the other side of the equation, there are over 13 types of contraceptive methods, dosage variations, and 200+ brands of contraceptives worldwide.
Just like with many other medications, if you take a formulation that is not suitable for you, you may experience bothersome side effects. The side effects from contraception can be as rare yet as severe as blood clots, or as common as irregular bleeding and low mood. The range is broad, including bloating, loss of libido, cramping, and acne.
Whilst conducting our patient research, and listening to many women and people assigned female at birth across the UK and the US, it was shocking to hear how frustrated many individuals felt about their contraception and the lack of information and education around the choices available to them:
There are too many options but they all have downsides - so unpredictable to know which one will be perfect for you and which will give you horrible effects as they affect everyone differently!
Moreover, for some individuals, a specific hormonal formulation will not be effective. This leads to the social, economic, and personal burdens of unintended pregnancies, and we remain unable to predict which individual may be at risk for these contraceptive failures. The current method for dealing with these contraceptive failures is simply trial and error, with little attention to symptom tracking, placing all of the risk on the individual themselves.
But what if things could be better? What if we could use personalised medicine to help predict which women are at risk for contraceptive failures and which women are at risk for those dangerous side effects? What if you had a precise test that could help women, people assigned female at birth and doctors make an informed and personal decision about the optimal contraceptive choice?
Dr. Lazorwitz’s research shows promise that genetic variants could help us identify the individual predispositions to contraception - including side effects, adverse reactions, and efficacy.
In one of the first ever pharmacogenomic studies with hormonal contraception, Dr. Lazorwitz identified a few genetic variants that may help explain why some women are at higher risk for contraceptive failures and specific side effects. In terms of contraceptive efficacy, he found that a specific variant in the CYP3A7 gene (denoted as CYP3A7*1C) appeared to increase the metabolism of the hormone etonogestrel that is released by the contraceptive implant. This increased metabolism or breakdown of the hormone could cause the drug to work less effectively. As the hormones used in modern contraception are all closely related, this genetic variant could likely have similar effects for any hormonal contraceptive method.
The CYP3A7*1C variant is found in roughly 5% of the population, most of whom would not be aware that they carry this genetic variant. With future research, we hope to validate these findings and finally solidify the first clue as to why some women get pregnant even when they use their birth control method perfectly.
But Dr. Lazorwitz didn’t just find genetic variants associated with contraceptive efficacy, he also identified a genetic variant in the ESR1 gene that was associated with significantly more weight gain during contraceptive implant use. As the ESR1 gene can modulate how the hormones from contraception affect the body, this variant seems to amplify the risk for weight gain while using hormonal contraception.
As we work to validate these findings this research offers tremendous potential to overhaul how healthcare providers approach contraceptive counselling and prescription. An individual with this specific ESR1 variant could be counselled that they are at much higher risk for weight gain with hormonal contraception, and all of the associated risks and morbidity that come with weight gain as well. They could then make a more informed decision about the right contraceptive method for them. This is the future of contraception that we hope to bring into this world.
Unfortunately, personalised medicine research in women's health is still in its infancy and there are many barriers that need to be overcome to make it a reality for women and people assigned female at birth around the world.
Whilst personalisation of therapies has become a major theme in the industry, it has been largely focused on biologicals, not single-molecule/generic compounds. And even when research shows some scientific breakthroughs, there’s usually quite a delay before these are implemented into clinical care due to the need to validate and duplicate scientific findings in multiple varied populations. Even once a finding has been validated across different groups, there are further delays to implementation due to a lack of guidance and regulation on how to use the information from such tests in practice.
For example, take a look at some well-known conditions such as heart disease. For decades, all patients were treated the same with the same treatment algorithm and medications. The initial studies in this field were primarily conducted with White men as the research participants. Only within the last decade have we determined that these treatment algorithms do not work equally for all patients. Thus, it is imperative that these studies be conducted with varied and diverse populations to ensure that we are meeting the unique needs of the individual.
In the case of bioinformatics, it requires very large samples of patients to be able to identify genetic variants or biomarkers linked to treatment response or disease progression. This increases the importance that a sample of patients or research participants is not a homogenous group. Even the genetic variants that we know have consistent effects on health may not always translate perfectly into a commercial test that is clinically useful for healthcare providers.
For example, the 23andMe “genetic health risk” report for BRCA1 and BRCA2 currently only checks for three disease-causing variants mainly relevant for people with Ashkenazi Jewish ancestry. This approach would miss approximately 80% of people with disease-causing BRCA variants in the general population as there are thousands of different disease-causing BRCA variants that the test does not check for.
Another challenge to mention is cost. Will the healthcare sector be able to find the incentives and create appropriate financial models to implement personalised medicine in daily clinical practice? Apart from costs of research and development of new tests, there are also high costs associated with its implementation and personalised treatments based on the knowledge acquired. These high up-front costs often mean that it may be difficult to prove the cost-effectiveness of these personalised approaches.
Fortunately, the costs associated with genome-wide sequencing and biomarker testing are decreasing every day, making the cost-effectiveness balance of personalised medicine start to swing in a more favourable fashion.
A large leap that may also help overcome the cost challenges of personalised medicine research is the development of health-system biobanks. Many universities and hospitals around the world are developing biobank systems for their patients whereby they can perform reflexive or preemptive genotyping for all patients seen in that system. These biobanks are quickly becoming some of the best data sources for large-scale personalised medicine research, with the UK NHS biobank being one of the largest thus far.
When implementing novel tests and innovative approaches, it’s crucial to manage patients’ expectations and involve them in the process. Communication and education are key. Careful framing of results and explanations around accuracy and complexity are essential to ensure that patients understand that the tests are not clearly predictive. Providers need to think carefully about what information will be disclosed and how, as well as think about what’s ethical and in the patients best interest.
Our medical education system across the world is evolving to include personalised medicine in the training of healthcare providers, but much of this education will remain on the ground among the medical workforce as technology and testing advances.
Collaboration between independent ventures, academic researchers, pharmaceutical companies and the medical industry is necessary to fully realise the potential of personalised medicine and overcome the challenges which will enable us to speed up the transition from raw knowledge to proactively improving lives.
Looking into the future
Is genetics the answer to personalised medicine in women’s health? It’s part of it.
At Dama Health we believe that the future of personalised medicine is through collating vast amounts of data - proteomics, microbiome, hormones, epigenetics as well as wearable data - and then making sense of it all, probably with the help of machine learning. Genetics is a great start and a foundation to which future biomarkers could be added. We are not quite there yet - we can collect the data but rarely can comment on what it actually means to the individual. We believe that personalised medicine can result in more efficient and equitable healthcare, improved control for individuals and truly proactive and preventative healthcare.
No one can predict the exact future of how contraceptive provision will look in 10-20 years. Perhaps, contraception will evolve and we may be even able to target ovary cells only with birth control medications?
Whatever happens, we envision that Dama Health will be a key stepping stone in that process as we aim to bring personalisation to how women, people assigned female at birth and their healthcare providers tackle the universal question of what medicine is the right medicine for you.