Could you briefly tell us a bit about your role at FIMM, and your current research?

I’m the Group Leader of the Translational Research and Personalised Medicine Group at FIMM. We work on haematological diseases, focusing mainly on blood cancers such as acute myeloid leukaemia (AML) and multiple myeloma.

The types of diseases we work with are relatively rare, which means that our research requires collaboration to establish good disease cohorts. In addition, the analyses we do are costly and require good access to analytical platforms, and therefore require a lot of resources; both in terms of infrastructure and funding. To help manage this, we work with other research groups with similar interests. At FIMM, we work closely with the groups of Olli Kallioniemi and Krister Wennerberg, who work within similar fields. We also work with the Computational Systems Biomedicine and Network Pharmacology groups of Tero Aittokallio and Jing Tang. In addition, we work closely with the FIMM Technology Center, led by Janna Saarela.

We also have a very good collaboration with the Division of Hematology at the Helsinki University Hospital Comprehensive Cancer Center and the University of Helsinki’s Haematology Research Unit, particularly with Kimmo Porkka and Satu Mustjoki. Together we have set up a platform to analyse patient samples from the unit, using our state-of-the-art infrastructure platforms at FIMM; namely high-throughput screening and next-generation sequencing. These platforms produce a lot of data, which take a long time to analyse, so having the support of several groups to work with these data is really important.

Thanks to these great collaborations, we have been able to accomplish quite a lot in a relatively short period, making an impact on patient care in ‘real time’.

What exactly do you hope to discover?

Our initial goal was to find new treatment options; especially for AML patients who are no longer responding to traditional therapies. The standard of care hasn’t really changed in over 40 years, so these are the patients who have really run out of options. Once the patient’s disease returns, clinicians have very few choices left. It’s therefore vital that we try and find new treatment options.

This research into possible new treatment avenues also provides us with a lot of molecular information. This is incredibly useful, as we can then use this information to try and better understand the molecular mechanisms of the disease. We can gain more insight into what is driving disease progression and drug resistance, which is really helpful in terms of future therapy development.

Where do you think the field will be in 10 years’ time?

I think we can certainly personalise treatment more, just by widening genetic screening. In terms of personalised medicine and drug development, the pharmaceutical industry is now looking to move much more quickly than it has in the past. The advancement of new drugs and therapies means that pharmaceutical companies also require matching diagnostic markers for their development. Therefore, when they try to get an approval for the drug, they now need to have diagnostic companion biomarkers as well. So, their research and development are also helping to drive further personalised drug development. I think the industry is now moving more in this direction.

What kind of barriers do you encounter?

In terms of implementing our findings in the clinic, access to drugs is really the main obstacle we encounter. Usually, when we test patient samples, we test them against hundreds of different compounds. Many of these compounds are approved, but a lot are still in clinical development, which means getting access to them can be nearly impossible. Ethics are also slowly starting to become more of a factor, mainly due to the fact that we are holding a lot of genetic data.

Do you see personalised medicine as the ‘cure’ for cancer? Is it the future?

Traditional therapies will still have place, but it’s important to be able to move into new areas, particularly where diseases like leukaemia are concerned. There are a lot of issues with traditional therapies. For example, chemotherapy not only targets tumour cells, but also healthy cells, which causes a lot of problems for the patient. The idea behind targeted therapy would be to just target the tumour and avoid damaging healthy cells, and also lessen the cytotoxic effects and adverse events that are traditionally associated with chemotherapy.

It is, however, important to point out that targeted therapies will only work for a very small sub-group of patients. Traditional chemotherapy will still be around until we can find better alternatives and have enough targeted therapies to cover everyone.

Could the principles of personalised medicine be applied to other diseases?

Definitely. There has been a real transition, even in the last five years, from using cell-line models to using real patient samples as the cell model for research. Animal models are, of course, still needed in some contexts, but in trying to understand the diversity of human disease, you really do need a model that really reflects that. Real patient samples are clearly much more effective in this context. I think this attitude has really taken off in the past few years; when I’m reviewing papers and research proposal applications for funding, more and more people seem to be using patient samples. I think this shows how ‘normal’ this is becoming. This trend in itself is a reflection of just how far the field has come in a short space of time; people are realising that medicine and research has to become a lot more personal.

Do you collaborate with other members of the Nordic EMBL Partnership?

We work quite closely with Bjørn Tore Gjertsen at the University of Bergen, who is also an NCMM Associate Investigator. AML is a rare disease; around 200-300 patients are diagnosed in Finland every year. We particularly focus on relapsing patients, which results in an even smaller cohort. To make progress, we had to look outside of Finland, and that’s when we found Bjørn Tore. He was very open and excited about working with us, and he’s become a crucial collaborator.

We started by exchanging patient material; we would conduct high-throughput screening on Bjørn Tore’s patient samples. We’ve since hosted members of each other’s’ groups, and now we have a lot of co-authored papers. We’ve also been able to access different platforms in Bergen (and benefit from Bjørn Tore’s expertise in these platforms), which has been hugely beneficial for our other studies.

Our work has now grown into a nice exchange of expertise, as well as of patient materials; this really demonstrates that one doesn’t need to always have platforms and infrastructures in one place. Collaborations like this mean that the scope of our work can incorporate so much more.

We’re also in discussions with Kjetil Taskén at NCMM about establishing a European wide network of expertise in functional personalised medicine and are in the process of applying for funding together for this.

What motivates you?

Helping people is a major driver for my research. To actually work on samples from real patients, with the prospect of genuinely helping them is incredibly motivating. This means that everyone in the lab, including those working in our core facilities, feels like they are really participating and making a difference. I think that with biomedical research, in particular basic research, it’s really important that researchers interact with clinicians to fully understand and realise what their research is contributing to, and what it means in a wider context.

Education is also a big factor. Seeing students in my group progress and become passionate about their projects, whilst working closely together is really inspiring – our work feels like it’s a genuine team effort.

Do you think collaboration is crucial for research?

I think research can sometimes fall into silos, with people focusing on just one project. I think at FIMM we have really broken that down to have genuinely effective and very collaborative projects that share knowledge.

I think research can become so much more efficient through collaboration; we can achieve results a lot more quickly through working together. I really think, and hope, that this way of working will become the way we ‘do’ research.