Traditionally, healthcare has been built upon the development and prescription of medicines on a one size fits all basis. Under this model, it can take tens of thousands of potential drug compounds entering a process that can cost billions of dollars and take up to fifteen years to complete to result in potentially only a single drug making it to market.
The majority of this cost and time is due to attrition. Learning the hard way which drug compounds aren’t effective, have unacceptable side effects, or work for only a fraction of the population. For this model to work from an economic perspective, and given the additional pressure of short patent protection periods, the resulting drug needs to be a blockbuster, generating billions of dollars of revenue through prescriptions to the largest numbers of patients possible.
Unfortunately, patients are not all the same. Many diseases have complex genetics that can present similarly, but could have very different outcomes and consequently, different requirements for treatment.
As soon as the Human Genome Project published its blueprint of the human genetic code in 2001, an important new approach emerged, one which involves understanding the underlying basis of disease, and through that knowledge, tailoring a treatment regimen to the specific genetics of that individual - Personalised Medicine.
The ability to sequence DNA has given us a much more accurate way to gain information about human biology. Over the last decade, the cost of sequencing a person’s genome has fallen rapidly and is now less than $1,000, making it affordable for the broad research community, and as a result tens of thousands of genomes are being sequenced every year. The challenge of interpreting this wealth of information is being addressed by ‘translational genomics’, which takes the information from the genomic sequences of individuals or populations and ‘translates’ it into meaningful actionable information for academic research and drug discovery.
Now tailored research programs, where early identification of patient groups for which the drug may not work or could be toxic, are being established based on knowledge of an individual’s genetic profile. This can be done in cells or in vivo models long before in-patient trials start, focusing efforts towards the areas of research most likely to be successful, reducing research time and enabling a model which is more efficient and cost-effective.
One powerful example is that of Crizotinib, a treatment for “non small cell lung cancer”, which took 7 years to get to market as compared to the normal 14 or more and with an investment of $500 million as compared with as much as $2.6 billion for standard drug development programs (Tufts Center for the Study of Drug Development, 2014).
Genetic screening now enables us to match the right drug to the right person at the right time. This is the essence of translational genomics and personalized medicine and Horizon is at the forefront of driving forward this powerful new model.
Translational genomics has become vital in the effort to drive personalized medicine, and the generation of precisely engineered cell lines and in vivo models is helping to lead the way. By editing the code of the human genome in functional human cells, the effects of genetic variation found in real patients can be reproduced in a laboratory setting, letting researchers ask important biological questions much earlier in the drug discovery process.
Initial attempts to engineer genomes used homologous recombination (the cell’s natural DNA repair mechanism) in order to generate transgenic mice. This approach, which worked in mice, wasn’t effective for the development of somatic cell lines due to the very low rates of homologous recombination in these cells, so alternatives were needed.
Since then, tremendous research efforts have gone into the identifying and refining tools to generate engineered somatic cell lines. These fall into two categories based on the cellular mechanism they take advantage of:
Each of these approaches has its own features and strengths and it is these differences are that make each best suited for addressing different gene-editing challenges. For this reason, Horizon has taken a ‘technology agnostic’ approach, developing deep experience and taking multiple licenses for rAAV, CRISPR and ZFNs, letting choose the right approach for any project, and letting us generate virtually any genomic modification with excellent precision and efficiency.
One illustrative example of the power of precisely engineered cell lines involves Iressa® (gefitinib). It was found through the course of its clinical development that only 4.8% of lung cancer patients – those with specific EGFR mutations – responded to Iressa therapy. Looking retrospectively, it was demonstrated using Horizon’s cell line pairs that EGFR mutant cells blinded amongst a broader panel of isogenic cells (EGFR wild type, K-Ras, B-Raf, PI3K) could predict the patient sub-groups who would respond or be resistant to Iressa therapy.
Another example is Erbitux® (cetuximab), a drug for the treatment of metastatic colon cancer. It has been shown that 40% of patients have a mutant K-Ras gene and these individuals are known to be ‘non-responders’. Currently, all patients with these mutations are being excluded from therapy. There are many different variants of mutant K-Ras however, and in a subsequent study published in JAMA in 2010, X-MAN Cell Lines predicted not all variants are equal and that there are patients who could benefit from Erbitux treatment who are excluded under current drug administration guidelines.