Over the past quarter century, scientists and pharmaceutical companies have trimmed the time off of new drug discovery and development by leaps and bounds. Unfortunately, it still takes about 15 years to develop a new drug, with costs going up to $800 million. This time frame and high price tag both reflect just how difficult it is to discover new drugs by converting compounds.
Why Does it Take So Long to Discover New Drugs?
The process begins when scientists identify a target molecule which is key to the disease or ailment they are trying to treat or cure. This is a highly precise process that involves studying the metabolic processes of the cell in two states: healthy and diseased. Although we are able to do this faster than ever before thanks to the successful sequencing of the human genome, there are still 30,000 human genes that offer different combinations for new drug discovery to take place within.
Once successful combinations have been hypothesized, scientists then must identify a lead compound that has the ability to change the target molecule’s action. This is one of the most time consuming steps of the process and even when the lead is identified and deemed to be “active,” it still might not be able to be turned into a drug. The testing process here is long and tedious, requiring the development of chemical analogs, synthesizing the compounds and then testing of the compounds until a viable drug candidate is found—if ever.
This can still fail during drug development with complicated toxicology and efficacy tests at any stage. Side effects can derail a once promising drug, whether it’s being tested on animals or humans.
New Trends that Look to Speed Up Drug Discovery
In order to combat this lengthy process, there are a number of new trends in drug discovery that look to cut costs through more effective processes while helping researchers and scientists sift through the massive amounts of data that are hiding potentially lifesaving drugs waiting to be discovered:
• Better Screening Taken from Biotechnology Industries. Using approaches borrowed from the biotechnology field such as rational drug design, combinatorial chemistry, and in silico experimentation via computers, scientists hope to make the drug discovery process more productive by identifying functional data based on human genome studies. The goal here is to quickly take data and turn it into functional knowledge to have a higher output of success while minimizing time and resources lost blindly testing poor leads.
• Screening More Samples Faster with Less Manpower. Of course, if you want to speed up the productivity of drug discovery, you’ll also have to handle and analyze more samples. If you want to do that without increasing the manpower (and effectively cutting some funding by nature), you’ll need new techniques for screening samples effectively. This is where High throughput screening (HTS) systems come into play. HTS systems can either be semi automated work stations or fully automated robotic systems that serve as highly effective liquid handling stations. These concentrate on filling, washing, rinsing and of course, reading characteristics of samples such as fluorescence and protein crystallization.
• Rational Drug Design. This has produced a high volume of drug discoveries already (such as the Tamiflu oral anti-influenza treatment) but we’ve yet to see the full power realized. Over the next decade or so, rational drug design—a process by which some of the randomness from the drug process is removed—will see big gains in popularity and usage. Using information taken from protein structures or collections of hits from HTS, small organic molecules can be optimized to speed up the drug discovery process.
• Automated Notes. Lab notes are crucial for finding out what went right and what went wrong during drug discovery processes. Unfortunately, these can be painstaking to make and even more painstaking to pour through. Automated software for lab notes is going to change the rate at which drugs are discovered, making it easier and faster to go through the process and evaluate the process afterward. Electronic lab notebooks are already available, helping scientists organize and translate their experimental and data notes. Some of these programs can even take local data and combine it with documents on the web in order to “ping” solutions and alternatives that scientists might have missed in the lab, providing another layer of thought to the drug discovery process.