Precision medicine is a healthcare approach that tailors treatment to individual characteristics, such as genetics, environment, and lifestyle. It moves away from the “one-size-fits-all” model* by using data to identify the most effective treatments for specific patient subgroups. This method has been shown to be transformative in areas like cancer treatment, where therapies are selected based on a patient’s unique genetic profile, and it’s going to spread to other areas as well.
In order to let precision medicine have an impact across the board, it’s key to be able to use many data points from a patient in order to draw conclusions on which the best course of treatment is.
This demands a number of things, among them:
an ability to efficiently (easy logistics and low cost) create data from an individual patient;
an ability to, based on the data, create new hypotheses and data models that help draw the right conclusions;
an ability to make data available across domains and geographies to improve/train and validate the models.
The first two bullets create a lot of room for new innovative solutions. Examples could be new ways of diagnosing, by unveiling new bio/-chemical/-electrical/-mechanical pathways that expose previously hidden important information that can be exposed by existing or new modalities. We see a lot of those kinds of solutions in the life science innovation system. Discovering and putting to use new patterns in existing data, by using new machine learning (or “AI”) mechanisms, has also resulted in a wave of new solutions - of which some surely have overpromised but others prove to deliver real value.
Given all this, it’s unfortunate that general data availability (the third bullet) remains suboptimal. The adage “data is the new gold” might have lead to** hoarding and the erection of barriers to sharing by actors that have managed to (or happened to) place themselves as data monopolies (even when your tax money paid for the data production), or grand designs by new actors that want to position themselves to “own” a new data category. Given the immense promise of societal benefit to data availability, and the fact that these data are derived from individuals within our societies, it’s maybe unfortunate that the adage isn’t “data is the new tapwater” instead - i.e. something that we have invested in on a governmental level (ensuring privacy and other regulatory controls where necessary), and made available as a basic infrastructural service at a low, low price to pretty much everyone. Imagine the number of innovations that could result from this!
Opinion piece by Petter Wolff.