The title of this post today is inspired by one of my bioinformatician science buddies on Friendfeed, Neil Saunders, who has a great blog that’s worth checking out.
Here’s a wonderful simplified picture of many of the pathways thought to be involved with different types of cancer and was shown by Dr Wafik El Deiry of Penn at the recent AACR meeting on colorectal cancer in Philly:
Source: AbCam (pdf download)
Imagine all those pathways that are overexpressed in any given cancer, some may well be mutated, most will be passengers, a very few will be actual drivers. Now imagine that all of them are lit up like a Christmas tree.
Not so easy to see the wood from the trees now, is it?
Think about drug development… how many people rush off and pick off one target and take a targeted therapy, either a monoclonal antibody or kinase inhibitor, combine it with standard chemotherapy and think it possibly might work, let’s suck it and see.
Ummm, no.
What are the chances of such a random unscientific approach actually working? Pretty low. Then we sit back and realise that the old models (animal, clinical etc) aren’t working any more and such an approach is no longer sustainable. The drain on resources, whether time, money or people is too high. The phase II/III attrition rate with that throw the mud at the wall approach is horrendous in oncology.
There is another way.
The smart researchers and companies are now using more modern, highly evolved animal models, doing more extensive preclinical research and thinking differently using a more holistic systems biology approach. They’re trying to figure out what the logical drivers are, which might suggest some logical combinations (think two unapproved targeted agents with an approved one perhaps) based on the constitutively activated or mutated targets, cross-talk, feedback loops and going into phase I research later with a more solid rationale.
The winners in this will be the companies with the most useful and broad pipeline who can mix and match more easily in this strategic pathway rather than tumour approach, with their own compounds than someone else’s. Collaborations on the pharma side are still relatively few and far between. They are often also a nightmare to manage, no matter what the original intentions were.
Change is already happening judging by the many enlightening conversations I’ve had this year with academic and pharma researchers, clinicians and commercial clients alike. This is great news and it’s driven by a greater understanding of basic research, better animal models, a panopoly of potential druggable targets and a broad, deep pipeline across the oncology companies as a whole. We just need to start putting the jigsaw together now and maybe we’ll see a difference in outcomes in the not too distant future.
The future may not be so far off as we think. The future is now.
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