Gene therapies are advancing much faster than our understanding of these technologies. This was the message from the Conference of the International Society of Computational Biology in Dublin which closes on Tuesday. More than 1,500 scientists whose work bridges biology and computer science attended the event, which had a major focus on stimulating public discussion about gene therapies.
"Dolly the sheep started the conversation many years ago but we are now in a position where scientists can actually find and repair genetic faults, which has enormous potential", says Denis Murphy, professor of biotechnology at the University of South Wales, speaking at a science education event at Trinity College today.
“These are exciting times in science, but we all need to engage in the conversation about what this means. The public are the consumer and we need to engage them in the conversation to find out what they want from gene research and how we can deliver that.”
The technology was rushing ahead with new techniques for altering genes. One called “CrispR” has the potential to identify and repair defective genes such as those responsible for cystic fibrosis.
Discovered by California scientists Emanuelle Charpentier and Jennifer Doudna, the “gene-editing” technique has already been used to alter laboratory cells to remove HIV and sickle-cell anaemia, Murphy says.
Prof Murphy leads a group of researchers from biology, mathematics and computer science who work on the "Big Data Problem". The first human genome was sequenced in 2000 at a cost of $1 billion. At the time, this was described as the dawn of personalised medicine, when we could each have our genetic makeup analysed and know exactly what our risk was for each disorder and what the best treatment for us would be, he adds. "While this remains the aim for gene researchers, this hasn't yet happened."
What has happened is that the human genome can now be sequenced for $2,000, likely to reduce further to $200 in two years. This has generated enormous amounts of information but in forms which cannot be sensibly translated into real-life advice for doctors, farmers and scientists.
“The amount of data being generated by our ability to cheaply sequence human genomes has outstripped our ability to understand and use it,” Murphy says. He and his team work on making mathematical tools to interpret this information and “turn it into something comprehensible and useful for medicine and agriculture”.
