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Precision cancer treatment: The future is now


Precision medicine is arousing a growing interest both within the big pharma and the public sector. According to the Personalized Medicine Coalition, in 2015 more than 25% of all new drugs approved by the FDA could be defined as personalized medicines. In the US, President Obama’s Precision Medicine Initiative has so far secured a $215 million funding for speeding up the development of tailored treatments.

Cancer treatment is expanding beyond the one-treatment-fits-all standards towards more and more targeted treatment options, where each person’s unique disease risks factors and causes of disease are taken into account. At least to a certain degree.

So where do we stand today with personalized cancer treatments?


Personalized medicine’s greatest strides so far have been cancer-related, and mutation-specific treatments for various conditions already exist. In many cancer types, genetic testing is utilized to determine whether a certain targeted drug treatment is likely to be efficient.

Potential target mutations can included those leading to improved cell survival, driving cancer progression, or present only in cancer cells and not in healthy cells, for example. The cell-growth related BRAF V600E gene, for example, is altered in 40 to 60 % of cutaneous melanomas. The mutated form of BRAF kinase can be specifically targeted with the kinase inhibitor vemurafenib, which has been approved to treat mutation-positive patients with metastatic melanoma.

As the options for targeted treatments are growing, online tools for selecting mutation-specific treatments are also being developed: as an example, a website for doctors and patients designed by MD Anderson Cancer Center’s Institute for Personalized Cancer Therapy allows the treating physician to search for approved drugs or clinical trials available to target mutations of a specific patient.


The methodology for collecting personalized data is developing with massive leaps – a fact that is starting to make customized cancer treatment not only accessible, but also affordable. Illumina, a genetic-sequencing company based in San Diego, has brought the cost for sequencing a complete human genome down to less than $1,000.

Besides genomic information, a massive amount of health-related data is already gathered by various health-related apps and wearables. So far, this data mainly aims at engaging individuals to actively participate in their healthcare, but it can also provide doctors with background for more customized treatment approaches: the Finland-based Noona, for example, has developed a mobile service providing cancer centers real-time information on their patients’ wellbeing.


Besides genetic testing and data collection with wearables, it is already possible to experiment drug efficiency on patients themselves – or at least on their cells. Culturing cells from the patient’s own tumor allows for the timely and cost-efficient drug efficacy testing for multiple therapeutic agents simultaneously.

In this manner, selecting the best anti-cancer drug or treatment is possible already before administration. As this approach is becoming more common, it will immensely improve patient safety, reduce treatment-related costs and minimize the often intolerable side effects.

As pointed out by the three examples above, personalized cancer treatments have already become reality. The growing amount of collected data will also require new approaches to judge which information is important and which is irrelevant, as well as secure data storing methods. Some ethical questions also need to be considered: international legislation on data ownership, for example, will become more and more relevant in the coming years.

However, the vast potential of personalized medicine greatly overpowers the challenges related to it. Admittedly, giving drugs only to those who are highly likely to benefit from them does bring along points that are hard to argue.

At their best, targeted treatments could:

  • Reduce the amount of therapeutic agent needed to achieve a desired response, which in turn reduces costs and minimizes side effects, improving the patients’ quality of life
  • Help to scale down hospital visits (and associated costs) as treatments can be given at longer intervals and in shorter regimens due to their higher efficacy
  • Minimize waste of valuable drugs (and reduce costs) as only the optimal target group of patients receives each given treatment
  • Allow re-purposing of old drugs for new indications, again reducing the huge costs involved in drug discovery


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