It has been a while since my last post and I wanted to make a slight change of direction for this one.

Most of my prior entries have been oriented around the needs of larger organizations in the life sciences dealing with such topics as cost reduction pressures, providing necessary computing infrastructure, supporting R&D, and managing legacy systems. I thought that for this entry I would focus more on the needs of smaller life science companies, especially those starting the process from concept to a marketable drug or device.

We are very fortunate here in San Diego to be one of the major bio-tech clusters in the world with nearly 500 companies ranging in size from small to fairly large. There are also a number of the big pharmas, like Pfizer, with R&D or other facilities here in San Diego.

The business model for small or startup bio-techs has changed significantly over the last few years. Many of these companies now operate in a very virtual mode with a significant number of the research and development and even administrative functions performed by outside vendors. This varies company to company but can include such functions as screening, toxicology studies, drug manufacturing, clinical trials, IT, HR, and publishing/regulatory submissions. These companies, like many startups, are operating in a cash constrained environment so every dollar not spent on internal IT resources can be directed to the science of drug development.

In regards to cloud computing what are the related areas of technology that these smaller firms can effectively leverage? Certainly outsourcing is not a new trend but many of these smaller bio-techs are keeping the core staff of their companies focused on their science and utilizing outside vendors and service providers for other activities as much as possible.

While many of these companies may be small their computational needs can be as large and complex as a big drug company.  The advance of genomics, high throughput screening, computational chemistry, and protein design requires that early stage bio-techs have access to comparable computation resources as their larger counterparts. Storage needs can also be somewhat similar. The data output of genomic sequencing consumes tremendous amounts of storage which small bio-techs simply cannot afford to acquire and manage.

The use of IAAS has become quite commonplace with smaller biotechs allowing them to gain access to the IT resources they require to further their drug development. The elasticity and pay-as-you-go model is very well suited to the needs of early stage bio-techs. They can save tremendous amounts of capital by utilizing off-premise computational and storage resources to support the daily R&D activities and for such things as backing up critical data and providing inexpensive disaster recovery capabilities.

SAAS is another area that is being actively adopted in bio-tech companies. Most of these companies simply cannot afford to acquire and support internally the IT resources required to run the business. Accessing needed applications via the SAAS model is a perfect way for these companies to utilize the software they need at a much reduced cost. This can range from scientific applications to publishing, document management, and even business functions such as e-mail, HR, Sales/CRM and Accounting. 

I am working with a number of smaller bio-techs in the San Diego area and they all have the use of cloud computing technologies as an integral part of their overall business and IT strategies. I am currently finalizing the planned activities for one of my clients to move many internal functions to the cloud. I will be sure to keep you all apprised of the outcome of that effort. Vendors who can provide cost effective services to these types of companies will have a distinct advantage in penetrating the life sciences market place as these companies expand.

So it is not just big companies that can leverage cloud computing but also smaller early stage companies that can take advantage of what cloud computing has to offer to cut costs, reduce complexity and ensure that resources are focused on the primary goals of the organization.