Rise of biologics

Nitin Sood explains the expansion of automation trends in life sciences.

“Automation will be a key component in reducing cycle time, developing high quality targets and getting quality biologic candidates into the pipeline faster”
-Nitin Sood

Can you explain current automation trends within the life sciences sector?
Nitin Sood. The automation trend we are seeing is a shift in emphasis away from small molecule lead identification with its larger and more static automation systems toward flexible, bench top stations to support target identification and the development of new biologic therapeutics, or NBEs. This is consistent with the broader industry move toward biologics and the need to have high quality and well-characterized targets. Biological drugs offer greater target specificity, improved safety profiles and open up new possibilities in disease treatment and prevention not addressable with conventional therapeutics. As such they are an attractive addition to the pharma portfolio, commanding a premium price with reduced competitive pressure, especially from the generic threat that looms for small molecule drugs.

Within five years half of marketed drugs are expected to be biologics, and the industry is moving to sustain and expand NBE discovery. We expect to see our business shift accordingly, moving to the earliest stages of drug discovery. Automation will be a key component in reducing cycle time, developing high quality targets and getting quality biologic candidates into the pipeline faster.

What are the challenges and benefits of expanding automation beyond HTS workflows and what tools can pharmaceutical companies use to achieve this?
NS. The challenge is in being able to understand the fundamental differences between screening for active chemical entities versus developing quality targets and viable NBEs. In order to address target ID and biologics discovery, automation companies need to begin thinking beyond simple throughput concerns to the more sophisticated idea of reducing cycle time. Reducing cycle time means a greater emphasis is placed on the quality and certainty of results, on the science that is driving discovery. That science changes rapidly and the automation must have the flexibility to respond. At Agilent, we are known for robust, low-footprint automation that can be easily repurposed as the need changes.

Another challenge is that reducing cycle time means having a deeper understanding of the science and the steps involved to getting a sound result. That pushes us to consider new applications and assays. In traditional lead identification, we essentially address one step of a workflow. The basic operation is plating compounds, transferring compounds to assay plates and reading. Now consider what goes into a target ID workflow. We have a customer doing functional genomics using a lentiviral system. They create vector libraries, produce virus, transfect cells and assay the cells. They use an Agilent BioCel system to automate the whole process, so the system does nucleic acid prep on the Agilent Bravo liquid handler, manages the pipetting and incubations involved in the transfection, through to high-throughput flow cytometry. The system has to orchestrate those various steps at the level of both hardware and software, which is quite impressive. This customer has cut their project time, gets high-quality data from the system and uses between one and two resources per project when they previously used eight to 12. And they were able to redirect those resources to develop the science that will give them a competitive advantage in the marketplace.

Which are the best methods for companies to use in automating their genotyping workflows and their siRNA screening?
NS. That's the beauty of a flexible automation platform. The science drives the automation, not the other way round. If it is feasible and sound scientifically, we can find a way to adapt and advance the automation to work with the application. And the automated methods we have already developed to support PCR and next generation sequencing are being leveraged by our customers to support the increasing investments in pharmacogenomics research. 

How do you see automation developing within the pharmaceutical R&D in the next few years?
NS. We see that there will be a continued emphasis on developing quality targets and biologic therapeutics. That will mean automating a variety of applications in genomics and protein analysis - something we already do but which we expect will take up the bulk of our business in the next few years as HTS investments level off. And we see public-private partnerships playing an increasingly important role, as more target development unfolds in universities and private research institutions. We're looking forward to the challenges and innovations that this will drive in the near future.

Nitin Sood is the General Manager of Agilent Automation Solutions and has served in this role since July 2009. Nitin brings a wealth of business experience and market expertise to his role. He has held leadership positions in leading life science companies including Applied Biosystems and Agilent Technologies.