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Personalised medicine: Breakthroughs and Challenges -  what are the next steps?

September 06 2018

In a previous article, we looked at why personalised medicine is a crucial step for healthcare and clinical research. The potential benefits of personalised medicine are substantial and include; better patient outcomes, better drug development, and major benefits for the healthcare system and society. However, the field of personalised medicine is still facing challenges in bringing new innovations to the market. In this article we look at breakthroughs in personalised medicine as well as challenges to overcome.

Find the previous article on personalised medicine here.

Breakthroughs in personalised medicine

Over the years, there have been several major breakthroughs in personalised medicine. Especially within oncology, where we have seen some important discoveries. One of the breakthroughs was Trastuzumab (Herceptin), a treatment for breast cancers that express HER2 receptors, which are encoded by the ERBB2 gene. This overexpression occurs in ~15-30% of breast cancers. Patients are only treated with Trastuzumab if a tissue test shows presence of HER2 receptors. This discovery initiated a shift in the pharmaceutical landscape towards more personalised medicine. In 2017 34% of all new therapies that were approved by the FDA were personalised medicines (source).

A more recent oncology drug that takes basis in a personalised approach  is Durvalumab; a drug used with a complementary diagnostic to determine the presence of PD-L1 in tumour tissues. PD-L1 is an immune checkpoint that prevents the immune system from attacking the body's own cells and is often expressed in certain cancers. Blocking PD-L1 allows the body's immune system to fight the cancer.

While oncology remain at the forefront of personalised medicine, there are also other diseases that benefit from this approach. For example, Batten disease, where Brineura is used for slowing down the loss of walking ability - It is used for patients with a specific subtype of the disease caused by the CLN2 gene. Another example is Austedo, which is used for the treatment of chorea associated with Huntington's disease. It is not used for patients that have a CYP2D6 poor metabolizer variant as it can cause prolongation of QT-interval.

Recent developments in personalised medicine

Currently, most personalised medicine therapies are based on pharmacogenomic approaches, i.e. therapies that use genetic information to predict treatment response. However, recent scientific developments also includes other diagnostic approaches, which focus on the phenotype - such as MRI and CT imaging.

One phenotypical diagnostic approach is pharmacometabolomics. With pharamacometabolomics information on metabolite fingerprints can be used to predict response to therapy. For example, it was shown that increased levels of low-density lipoprotein–derived lipids were predictive for treatment toxicity with capecitabine in patients with colorectal cancer (source). This type of diagnostic can be valuable for diseases where factors that influence the phenotype of the patient play an important role in the development of the disease and in the response to therapy (e.g. type 2 diabetes). However, it is important to note that despite the scientific research being done companion diagnostics that measure phenotypical markers are scarce on the market at the moment. 

Challenges in implementing personalised medicine into clinical practice

While we have seen some important developments in personalised medicine, there are still several barriers delaying the implementation of new innovations in personalised medicine in clinical practice. These barriers include;

  • Costs of sequencing a genome are still high, although the price has gone down in recent years;  
  • Misinterpretation of genetic information: more geneticists are needed to process all the data or doctors will have to be able to interpret genomic data and make recommendation based on it (source);
  • Lack of integration of genomic data into electronic medical records (source);
  • A clear demonstration of the value of personalised medicine is needed so that healthcare providers and payers both understand the added value of personalised medicine (source);
  • A focus on cost of therapies (typically high for personalised medicines) rather than the added value (the overall benefit for the patient's health) (source).

At a conference on personalised medicine organised by the European Commission, it was discussed how to better bring  innovations to the market and give patients access to the new treatments.  One important step, is to create more awareness about personalised medicine, so that both healthcare providers and payers understand its added value. There is also a need to integrate Big Data and ICT solutions, in order to process the wealth of data, which personalised medicine will provide. In addition, we need a shift towards preventative care and a change in the way clinical trials are conducted. Patient reported outcome statistics need to be integrated in clinical trial design. Clinical trials should incorporate biobanks so that retrospective improvement of existing treatments can take place based on genotype/phenotype data. You can read the full report by the European Commission here.

Next Steps 

A new EBE-EFPIA study (10 July 2018) came up with 5 policy recommendations to help bring personalised medicine closer to market:  

  • A coherent prioritisation of personalised medicine that goes hand in hand with existing health strategic plans; 
  • A continued emphasis on better management of care, coordination of expertise and resources to ensure an adequate “personalisation of care”;
  • A continued investment and cooperation in next generation testing infrastructure (such as molecular genetic laboratories) as well as developing dedicated funding pathways to ensure access to diagnostics;
  • A consistent diagnostic testing infrastructure throughout Europe;
  • Better alignment of data requirements between regulators and health technology assessment bodies to improve evidence development and facilitate the value assessment process.

Are you ready to take your research in personalised medicine to the next step?

Here at ttopstart, our life science consultants and project managers are experienced in projects with a focus on personalising patient treatment, such as BigData@Heart and  PIONEER, a project managed by ttopstart that will harness the potential of big data and big data analytics as a means to ensure optimal personalised care for European prostate cancer patients. Fill out the form below to get in touch with us and discover how we can help your project become a success.

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