He/she will likely need to consolidate a range of IT-related activities that have formerly been ensconced in other components of the business. Additionally, creating shared standards for future hardware, software, and development will be important for supporting continued rapid growth scalably and effectively. Finally, providing a robust platform for data integration, analysis, and visualization across the complete range of data available to the company (both internal and external) will provide a means for stakeholders across the organization to understand and manage the growing company.

Consolidating and standardizing IT activities across an organization - even a small one - can be a daunting and complex effort. This is especially true when existing stakeholders already have significant positions and ownership in the current state of the IT infrastructure. One of the earliest and most critical moves that the new biotech CIO can make upon taking up his/her new position is to coordinate (and potentially consolidate) traditional IT (typically in charge of the physical and logical computational resources of the company) with scientific computing functions such as bioinformatics and computa-tional biology. Differences to be resolved ranges from the mundane-like choices of computing platform to more complex challenges like standards and governance. Starting by developing an understanding of these issues at the outset, a biotech CIO will need to carefully manage how the groups work together, ensuring that their members share common goals, and work together to develop shared approaches and interfaces, even if significant differences remain in underlying phi-losophy and approach. At Good Start Genetics, we have spent months working on shared standards for software architecture, data/metadata, development lifecycle, et al., along with the tools to support those efforts. By leveraging all aspects of IT, and through cultivating leadership from scientists outside of IT, shared infrastructure and standards can emerge via a light touch of guidance, rather than forced integration.

Accommodating the needs of this wide range of biotech stakeholders, as well as the rapidly-growing and fast-changing business, demands scalable and flexible computing infrastructure. Not surprisingly, many biotechnology companies are increasingly turning to established cloud providers such as Amazon, Google, Microsoft, and others for a ready supply of on-demand computational infrastructure. At Good Start Genetics, we have leveraged the availability of HIPA A Business Associate Agreements with Amazon and Google to enable offsite high-per formance cluster computing as well as more conventional Windows and Linux servers to support day-to-day business needs. By making use of standard virtual machine builds for company functions, a fast-growing biotech company can allocate computation between on-premises and external computing resources as needed to balance usage, costs, and time. Even small companies can quickly field amounts of computational resources that would have been unheard of just a few years ago.

Finally, providing data and analytics to stakeholders throughout the organization can yield significant benefits of transparency and flexibility to business users well outside of IT. New platforms and tools are being continuously developed which can enable data from a wide range of sources to be integrated, analyzed, and visualized. In biotech, this data typically includes the results of scientific and biomedical research, but can also include sales data and competitive intelligence. At Good Start Genetics, we have found that integrating data from a wide range of sources can yield important new business and scientific insights. Combining enterprise-wide tools like MongoDB, Neo4J, and Tableau along with integrated sources of scientific and business data has provided a means for technical and non-technical stakeholders to collaborate in the development of new insights, and to share those insights through convenient dashboards. To facilitate this, we have constituted an in-house Data Science group whose mandate is to both answer the complete range of analytics questions, as well as develop the necessary scalable infrastructure to support the underlying data integration and analysis.

By combining the emerging range of computational and analytics tools with a thoughtful approach to managing the complex stakeholder environment, a biotech CIO can navigate a fast-changing environment, and manage the growth in scale that comes with success. I have loved my adventure as a biotech CIO, and will continue to look forward to the challenges and changes ahead.

Check This Out: Top Biotech Solution Companies