“Harvard spinoff promises genome sequencing for $30”

This was the headline from FierceBiotech Research, a biotech journal. It’s also a game changing development for the industry as a whole and part of a bigger trend of personalized cancer medicine. The first time scientists sequenced a human genome it cost $ 3 billion. Then it went to $ 6 million (2006), then $ 60,000 (2008), in June 2009 Illumina pushed it to $ 20,000, Nov 6 2009 Complete Genomics promised $ 4,400. The prediction for the coming year? $ 1,000 in 2-3 years and further down to $ 100 in 5-10 years.

This is where a Finnish startup MediSapiens comes in. MediSapiens is the world’s first software for personalized cancer medicine in oncology clinics and new drug development. The company just recently completed € 0.8 million seed round investment from Veraventure, ETFIII advised by Eqvitec Partners, VTT Ventures and Lifeline Ventures.

MediSapiens hosts world’s largest unified gene expression database. This enables scientists to understand the role of human genes across all human tissues and diseases to be applied in helping oncologists on treatment strategy selection, and biopharmaceutical companies in developing next generation personalized medicines.

The latest research demonstrates that every patient’s cancer is a complex, personal combination of genetic mutations and abnormally expressed genes. The MediSapiens software gives personalized and clinically-applicable insight into each patient’s cancer.

I talked to Timo Ahopelto, a Lifeline Ventures partner, who is working as VP Strategy for MediSapiens to get my head around the emerging trend.

1. What are the big trends in cancer treatment personalization today?

First, cancer is a deadly and unbeaten disease. 1/2 of us alive today will get it, and 1/3 will die of it. There is lot to be done in the field of cancer medicine, and we need a major shift in today’s diagnostics and therapies to win the battle. The main treatment strategies – chemotherapy, surgery and radiotherapy – are 50 to 100 years old already.

Second, cancer is a genetic disease on cellular level and we are just starting to understand it. This means that your genes – how they are mutated and how they work – define how your cancer develops. At the same time the latest research – such as The Cancer Genome Atlas funded by NHI – demonstrates that every cancer is a unique combination of these mutations and abnormal gene functions, and one by one for every patient.

This only leads to one conclusion being adopted by the industry: to treat cancer, every patient needs to be understood individually and on genetic level.

2. How is it done today?

Pathologists use microscope – for a genetic disease 10 years after we have sequenced human genome.

In addition, companies like Agendia and Genomic Health have developed dedicated chips that measure typically 20-80 genes for a single cancer type to support a single treatment decision. These tests stratify patients, they don’t personalize medicine. For complex disease this stratification is not very optimal.

Very interestingly, the industry pioneers announced just some days ago from Foundation Medicine, a startup raising $ 25 million to bring genomics into routine use by oncologists. This is the next wave that MediSapiens represents: bringing through understanding on patient’s genetic signature to clinic.

3. How can software and data change it?

No-one is using software and no-one is using large-quantity data. It is in fact amazing that all other industries are moving into software and medtech stays in hardware.

So how we work and how software can change this?

We can tell all genetic differences of an individual patient compared to world’s healthy and cancerous patients.

We take industry-standard genomics profiling results of single patient, and analyze those against a reference database of 15,000 patients’ genetic signatures and clinical outcomes. This is revolutionary — as cancer is defined by how our 20,000 genes work, personally with everyone of us, the only way to understand the disease is to see what is broken with each patient, one by one. And a natural way to understand this is to compare statistically: it is like Newtonian physics (old school of cancer diagnostics) compared to modern physics (based on statistically understanding complex phenomena). Our benefit is to have all information available, all anomalies detected and against the latest science embedded into the software more flexibly than dedicated hardware units. Software can also visualize this to oncologist for clinical use.