While the run rate for new drug approvals has shown some improvement during the past couple of years, with more than 40 new molecular entities being approved by the FDA last year, drug discovery and development still remains an ever-increasingly costly, time-consuming and risky undertaking.

That was confirmed by R&D leaders participating in a recent Tufts Center for the Study of Drug Development (CSDD)-hosted roundtable.

Ken Getz, associate professor and director of sponsored research at Tufts, CSDD said, "Drug development cycle times have not gotten faster, costs continue to increase and drug development has become riskier than ever with only 11.8 percent of products that enter clinical testing receiving regulatory approval, about half the rate of the 1990s."

The reward to be able to reduce the time and costs of drug development would be huge. According to CSDD research, Getz noted, "a 10 percent improvement in cycle time and success rates can shave $634 million off the total capitalized cost of $2.6 billion required, on average, to bring a new drug to market."

COST EQUATION

Reducing the cost equation dramatically may not be too far off for biopharmaceutical companies. There is a gathering groundswell that cloud-based supercomputing has developed to a point where it can begin to make sense of the massive amounts of data being generated from molecular biology and genomics. In addition, computer programs are being developed that can screen and identify promising drug leads in a fraction of the time that it would take by using traditional medicinal chemistry routes.

Ed Addison, CEO of Research Triangle Park, N.C.-based Cloud Pharmaceuticals Inc., said a quiet metamorphosis is occurring where high-performance computing is beginning to play an increasing role in allowing biopharma companies to cut the time they spend on research and development and identify promising lead candidates to move into testing.

Cloud computing is a paradigm shift whose time has come. And a confluence of factors are responsible, Addison told BioWorld Insight.

The most notable driver is cost. "It is now one-10th the cost to perform a de novo design of a drug than it was about five years ago," he said.

In addition, back in 2005 the main approach for computational drug discovery was docking algorithms since they required less CPU hours compared to quantum chemistry. The trade-off was inconsistent results due to inaccurate prediction of activity.

Fast forward to today, designing new drugs that bind to a specified protein target requires finding the best molecule in a vast chemical space.

QUANTUM MOLECULAR DESIGN

Cloud's approach is to use its quantum molecular design, which discovers novel drug candidates by searching the virtual space of millions of molecules, accurately calculates binding affinities between targets and selected candidates, and filters them for toxicity and drug-like properties. The process combines high-performance cloud computing, quantum mechanics/molecular mechanics, and molecular property simulation, which dramatically improves upon traditional drug discovery and design methods.

The company's business model is a hybrid between a contract research organization and a biotech. In order to succeed, Addison noted, you need to conduct plenty of projects, and Cloud Pharmaceuticals is well along that path.

In August, for example, the company entered a partnership with Genomeon LLC, a start-up genomic diagnostic and drug target discovery company. Genomeon's technology represents a systematic effort to farm the approximately 1 million microsatellites in the genome to identify potentially informative patterns of variation between healthy and diseased individuals and to identify potential new drug targets. To date, it has analyzed the microsatellites in more than 10,000 genomes. The partnership research involves Cloud accessing Genomeon's microsatellite technology to mine next-generation sequencing data so it can identify novel drug targets and companion biomarkers. They can then quickly design inhibitors against selected targets to bring fast, precision treatments to cancers and other genetically influenced diseases.

Cloud is also working with Therametrics, of Stans, Switzerland, for orphan central nervous system diseases such as Huntington's disease, amyotrophic lateral sclerosis (ALS), progressive supranuclear palsy and frontotemporal dementia.

Therametrics will employ its technology, which can scour the literature to identify novel protein targets, which are produced by the genes responsible for certain pathologies. Cloud will apply its quantum molecular design process to design small molecular compounds and peptides that inhibit the activity of those targets.

Cloud is not alone in this paradigm shift toward in silico drug discovery.

San Francisco-based Verge Genomics Inc., for example, plans to identify and design drugs for neurodegenerative diseases using proven network algorithms to map the dozens or hundreds of genes that cause a given disease and then pinpointing the most promising drugs to target those genes – at one-1,000th the cost of the "hit or miss" methods currently used. (See BioWorld Today, Oct. 29, 2015.)

The company's three initial disease targets are Alzheimer's disease, ALS and Parkinson's disease; and its vision is that genomic data, combined with knowledge of the biological underpinnings of neurodegenerative disease, offer a unique opportunity to develop effective treatments with unprecedented efficiency and precision.

Provo, Utah-based Tute Genomics, which provides a cloud-based genome informatics solutions to help diagnostic labs and health systems process next-generation sequencing data, reported earlier this month that it had acquired the key assets of Knome, which was co-founded in 2007 by renowned geneticist and Harvard professor George Church, who recognized a substantial need for genome interpretation technology as the cost of sequencing was rapidly decreasing. Tute will integrate Knome's third-generation knoSYS technology, a genome interpretation software platform, with its cloud-based genome informatics and clinical reporting platform, to deliver flexible, scalable and secure informatics solution for genome-guided medicine.

Editor's note: In next week's issue, the second part of this article will look at how companies are taking advantage of cloud-based computing to improve drug development.

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