Personalised medicine: coming soon to a clinic near you

Personalised medicine will disrupt every part of the healthcare sector, from R&D and clinical trials, through diagnostic testing to regulation and healthcare provision (whether insurance-based or through national systems, such as the NHS). This will be driven by economics and improved medical outcomes. A key challenge will be the storage and analysis of huge quantities of patient data.

18 April 2017

Mona Shah, Head of collectives

Risk of disruption = high

In the late 1990s, advances in research and development (R&D) promised to revolutionise the pharmaceuticals industry. Scientists were on the cusp of mapping the human genome, which is the DNA ‘genetic barcode’ containing the information to build, repair and run our bodies. It also contains clues about things that might go wrong as we age and which medicines might work best for us.

It was believed this would enable us to take a big step towards personalised medicine (also known as precision medicine) and away from the existing ‘one-size-fits-all’ model. A 2001 study showed that only 40% of patients benefited from commonly used drugs for asthma and diabetes (FDA, 2013). Similarly, fewer than half of migraine sufferers find their tablets to be effective.

Surely by designing medicine based on an individual’s genetic map, science could markedly improve our quality of life. Nearly 20 years later, is personalised medicine a reality or was it just hype and wishful thinking?

What is personalised medicine?

The EU describes personalised medicine as “providing the right treatment to the right patient, at the right dose at the right time”. By taking into account genetic factors, doctors will be able to recognise at diagnosis which patients are more likely to benefit from a particular treatment. The outcome of this is wide-ranging — increased wellbeing, fewer side effects and lower costs. In contrast, the current model is essentially based on trial and error.

For example, a patient with high blood pressure could be prescribed one of many drugs, based on their height, age, weight and lifestyle. If the patient’s blood pressure reading does not fall, an alternative drug will be prescribed and the process repeated until the result is positive. For premature babies, a hospital needs to provide intensive care as it works out which drugs will work best. This could cost up to $20,000 a day; running a genomics panel would result in more efficient treatment and a shorter stay in hospital (Shobert, 2017).

In light of the above statistics, an improvement in the efficacy of the drugs we take (how effective they are) would have a huge impact. The annual NHS drugs budget is £12 billion: if just 25% of that is wasted on ineffective drugs, these cost savings alone make personalised medicine an attractive prospect.

Why is personalised medicine on the agenda now?

The cost of gene mapping has fallen exponentially, making ‘designer medicine’ possible for all. Furthermore, it is now rarely necessary to map the whole genome: a panel test for a smaller sequence is possible, as is a test for one or two genes using a handheld device.

In 2013, Angelina Jolie underwent a double mastectomy after having a genetic test that showed she had a mutation in the BRCA1 gene increasing her likelihood of breast and ovarian cancers to 87% and 50% respectively. After the mastectomy, her breast cancer risk dropped to 5%.

The first human genome to be mapped cost approximately $3 billion; by 2007, this had decreased to $2 million; Ms Jolie’s test was estimated to cost $10,000 in 2013; and today it costs just $1,000. BGI, a Shenzhen-based company at the forefront of nano-chip technology, believes it can drive the cost down to $200 (Shobert, 2017).

The impact of predictive testing varies for different inherited cancer conditions. For example, ovarian cancer is still relatively hard to screen and treat, yet keyhole surgery is relatively straightforward. As a result, after having their families, surgery is taken up by over 80% of those identified as at risk. In contrast, because the screening and treatment for breast cancer are better, yet surgery is far more severe, take-up is only around 33%.

As well as prevention, personalised medicine is also already used in treatment with positive results. Genetic testing has transformed the treatment of lung cancer: there is much faster testing for far more people, and it is now almost routine. A study by the M.D. Anderson Cancer Center showed that patients who received targeted therapy had a much higher response rate of 27% compared with only 5% for a non-targeted approach (Tsimberidou & Kurzrock, 2011).

A question of cost

Immunotherapy (see box 2 on page 7) shows how important genetic mapping is to ensure patients get the right treatment. Such applications will surely increase given testing costs have fallen so rapidly.

But what about the cost of drugs? At present, through R&D, pharmaceuticals companies identify potential drugs and conduct a series of expensive clinical trials that test efficacy and safety. Eventually, if the data are sufficiently compelling, they seek approval from the appropriate regulator, such as the US Food and Drug Administration (FDA) or the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK.

If approved, they can be manufactured exclusively by that company until its patent expires. Then generics companies can apply to produce them, often driving down the price dramatically as the cost is in R&D, not manufacture. Patents usually extend for 20 years, but R&D and the approval process can eat up the first 12 to 15 years, leaving the drug company with only a few years to ramp up sales by convincing doctors and patients of the product’s superior efficacy.

As a result, only one in five approved drugs recoups its development costs (and many aren’t approved, resulting in lost R&D expenditure). Many pharmaceuticals companies survive on the supranormal profits from ‘blockbuster’ drugs and even these have proved more elusive in recent years.

As we have seen, however, a key element of personalised medicine is that the use of drugs will be reduced to those patients for whom they will be efficacious. Pharmaceuticals companies could view genetic testing as the enemy as it is low cost and is likely to reduce the addressable population for a specific drug. They fear being squeezed at both ends by high R&D costs and lower revenues.

Genetic sequencing could result in the end of blockbuster drugs as new medicines drive higher efficacy rates, but for smaller groups of patients. If unit sales fall materially, drug companies would have to increase their prices accordingly, offsetting the cost savings of personalised medicine to the healthcare provider. To avoid this, they must be incentivised to invest in R&D without increasing their prices — one solution would require a radical change in the regulatory model.

Unlocking the human genome
The cost of mapping the human genome has fallen rapidly

Regulate to cultivate: the role of the regulator

If regulators can bring down the cost of developing drugs, pharmaceutical companies will be more likely to embrace bespoke medicines. For example, regulators currently require large populations to be tested in expensive clinical trials to ensure that any safety issues show up in the data. By trialling drugs only on those that have specific genetic or other attributes, clinical trials could be smaller and more targeted, and would therefore be far more efficient.

The FDA has historically believed the greater the number of subjects in a trial, the greater its confidence in the results. For example, a recent cervical cancer vaccine called Cervarix was tested on 30,000 young women (CDC, 2016). Such trials are extremely expensive. The FDA’s 2013 paper on personalised medicine seems to be aware of the challenges of this approach. 

Smaller studies can be accurate if the tested population is very similar — genetic testing is the key to this. The FDA has set up a genomic reference library for regulatory agencies to compare results from different sequencing platforms. This is a step towards overcoming the limitations of smaller drug trials. There is an interesting link to blockchain (discussed on pages 22—25) here because it could facilitate the secure sharing of patient data. If smaller trials could be conducted more quickly, pharmaceuticals companies would also enjoy a longer period of patent-protected sales. Equally, an increase in patent length to 22 years or more could offset the decrease in unit sales.

Improved safety is an important factor in personalised medicine. From the regulators’ focus on safety, it would be reasonable to imagine that all approved drugs are safe today. However, in 2015, 6.5% of all NHS hospital admissions were from adverse drug reactions. With a median stay of eight days, this accounted for 8,000 NHS beds at a cost of £1 billion. 

Pharmacogenetics is a new field of medicine that has important implications for healthcare providers. It relates to how our genes affect our response to certain drugs. Scientists believe that 30—50% of this may be genetically determined, but that it could be up to 100% for some drugs. Where kidney function tests to monitor dosage levels are currently routine, genetic tests are not. In future, such tests may allow doctors to tailor doses for maximum efficacy and minimum side effects. For example, abacavir, an HIV drug, causes serious side effects that may cause death in 7% of patients — testing has greatly reduced such reactions.

Ironically, this highlights a disruptive challenge of moving to personalised medicine — much of the value generated comes from patients not taking a certain drug, which saves money for the healthcare provider (whether it’s a national health service or insurance company), avoids adverse reactions and stops time being wasted while taking ineffective drugs. Yet diagnostic tests are now very cheap, while drugs remain expensive.

The regulator could alter its current practice by approving a screening test and corresponding treatment at the same time. This would align the interests of the drug developer, diagnostic developer and the healthcare provider. Our view is that partnerships will develop between drug and diagnostic developers. Although the potential profits from such a partnership are higher for the drug developer, for pharmaceuticals companies to maximise their profits they must embrace genetic testers. 

To insure is to cure

As we have shown, the biggest disruption from personalised medicine is in healthcare economics. Can the obvious health and financial benefits be realised within the current system or will there be big winners and losers?

In the US, we believe change will be driven by the healthcare insurance sector as it will be the beneficiary from greater efficacy at a lower cost. Within reason, it is also incentivised to benefit from expenditure today to achieve future cost savings. If different treatment options are available, insurance companies will pay for a test to identify the best course given a particular patient’s genetic make-up. They could therefore play an important role in selecting the most cost-effective tests. On this basis, they are a bridge between the diagnostics and the pharmaceuticals companies.

Under the new regime of personalised medicine, however, will the concept of ‘shared risk’ become irrelevant? This is the traditional foundation of insurance, but if affordable tests are able to give us more accurate predictions on the likelihood of contracting life-threatening conditions, this could feed through to insurance premiums. Those with ‘healthy’ genes could pay far less — the opposite would also apply.

How would insurance companies view rare diseases or those where personalised medicine is not available? There are many questions here we cannot answer, but it would be a mistake to think that healthcare insurance companies are less relevant in a world of bespoke medicine. We believe they will be instrumental in driving the transition to the new system and may well remain central to its delivery. 

The same ought to be true of national healthcare systems, such as the NHS. The cost benefits from better treatment outcomes, lower spending on ineffective drugs and a great reduction in adverse drug reactions ought to make personalised medicine a ‘no brainer’, but centralised healthcare systems are very cumbersome and slow to adapt. For example, the NHS works on annual budgets: it isn’t designed to ‘invest’ this year to achieve cost savings that might accrue in the future. While thousands of women have now benefited from preventative treatment like Ms Jolie, could the NHS cope if this approach was applied across all diseases?

It is also ‘siloed’ — that is to say, different parts of the NHS find it difficult to communicate, let alone collaborate in order to derive future economic benefits. At present, for example, tests can only be ordered through a clinical geneticist, even if the data is required by a cardiologist to benefit his or her patients. 

The data challenges 

Other than the economics, the biggest challenge for healthcare systems will involve data. The capacity of organisations such as the NHS to handle huge quantities of data is a concern. A file containing genetic data for just one of us is almost a terabyte in size. Cloud computing will take a key role in genetic sequencing, but the computing power required to process this data will be huge. Technologists may argue that the era of ‘big data’ is fast approaching, but organisations have to be resourced with staff and technology to store and analyse these data, and direct their resources accordingly.

There are also huge questions about data usage and protection. The US Genetic Information Nondiscrimination Act was passed in 2008 to stop genetic information from being sold on to other businesses and insurers. Nevertheless, in future will patients have the right not to disclose particular personal health information to insurance companies?

Again, there is a possible link to blockchain because the secure storage of genetic information is central to patient privacy. Although patients’ genetic information must remain secure, there are strong positives to the data being shared among healthcare professionals. The cryptography within blockchain can ensure data is secure, yet easily accessible. 

Governments and insurance companies need to start thinking about solutions because personalised medicine is not far away. In 2012, the UK established the 100,000 genome project, making it the first country to sequence 100,000 complete genomes and start to link it to long-term health and hospital data. An impressive start, but can this high-profile research project become part of everyday medicine and healthcare management?

Conclusion: striking the genetic jackpot

Stratistics MRC claims that personalised medicine accounted for $94 billion of sales in 2015 and will rise to $178 billion by 2022. How these drugs are used, what they cost and how they are regulated are all questions that must be resolved for them to become mainstream. We believe it will be insurance companies in the US and, to a lesser extent, national healthcare systems in Europe that play the pivotal role in eventually making bespoke medicine ordinary.

There are currently 2,500 clinical trials taking place for immunotherapy alone. On this basis, it is timely to look at personalised medicine. However, it is still early days for this investment theme. Pharmaceutical companies that have strong pipelines in immunotherapy or other areas of personalised medicine look well placed. In contrast, those with weaker pipelines and large sales forces may struggle in the short term as they restructure.

It may be that the biggest winners from personalised medicine are the healthcare insurance companies. However, to maximise their profitability they need to transform their business away from the concept of ‘shared risk’. There will be winners and losers; some insurance companies may shrink in order to become more profitable. 

Although there are many obstacles to its adoption, scientific breakthroughs and exponentially increasing computing power mean that personalised medicine is coming soon to a clinic near you.

Beating cancer through our own immune system 

Scientists have known for decades that immune systems are relevant to treating cancer, but have only recently identified how tumours evade attacks on the immune system.

T cells are a key part of our immune system. They multiply when germs are identified to defend us from disease. They can over-multiply, so we have immune checkpoints in order to prevent autoimmune attacks on the body’s own cells. Tumours, which arise from cancer, are problematic because they pressure the immune system to stop attacking the cancer cells. By blocking the immune checkpoints from interference, patients can fight the cancer; this is immunotherapy. The attraction of immunotherapy is the patient’s own immune system does the work, so there are far fewer side effects than with chemotherapy.

Not all patients respond to immunotherapy, however, as it only recognises pure expressions of the PD-1 protein on T cells. In humans, it is encoded by the PDCD1 gene. By testing for this, oncologists can identify whether patients will respond to immunotherapy or other treatments will be necessary.

Blue-sky thinking: healthcare in 3D 

Imagine if you walked into Boots with your prescription and, instead of the pharmacist selecting from aisles of drugs, a 3D printer was used to print your bespoke tablets.

The use of 3D printing is already common in the production of prosthetics, particularly in arms and implants, and customised hearing aids. Researchers at Harvard University have just printed live cells, which include different types of tissues, such as skin, liver and cartilage, and can use them to test medicines. In the future, it may be possible to print new organs using a patient’s own cells.

The idea of a 3D printing pharmacy is not farfetched if genetic sequencing becomes commonplace. Your doctor would prescribe bespoke medicine in the form of a chemical recipe for the 3D printer to make a tablet.

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