Drug developers face substantial risks during the R&D process, and these are exacerbated when working with increasingly complex modalities and therapeutics. The nature of the process, particularly when developing therapeutics for smaller populations, as with rare diseases, also means that R&D is geographically dispersed.
Given these challenges, the industry has intensified efforts to speed drug development. New technologies have the potential to improve the process and allow companies to do more with their R&D data.
“The pharma industry is very focused on improving patient outcomes and this translates into curiosity: How can we go faster, do better, provide more effective therapies,” says Alan Millar, vice president of business development at TetraScience, a company focused on R&D data cloud solutions for the life sciences industry.
The challenge, he says, is overcoming the many barriers to finding, sharing and collaborating with the scientific data produced by the R&D process.
Here, Millar talks about the importance of an open platform for enabling scientists to do more with their data, the growing commitment across the industry to collaborate, and how building a network of industry providers can shake up the way data is used, shared and expanded on.
PharmaVoice: What are the biggest challenges companies face with accessing and making use of data?
Alan Millar: One of the biggest issues is the way data is produced and stored, with various vendors using different formats and often storing the data within on-premise solutions. The challenge is to integrate the different infrastructures used to produce the data and centralize it on a cloud-based platform, then engineer that data to take it from that multitude of different formats and produce a harmonized data format. The problem those different formats present for scientists is that typically there will be extensive manual transcription involved to convert data into an appropriate format with which the data can be shared or worked with. So, it's not unusual to see scientists spend a significant amount of their time transcribing scientific data, even into Excel spreadsheets, purely so that they can access the data and work with it. That’s tedious and it introduces significant opportunity for transcription errors.
The next question is, how do you transfer the data to a collaborator? As the volume of data increases, the challenge only increases, and as pharma moves to a more decentralized model for R&D through use of contract research organizations, the collaboration becomes even more complex since that partner could be on the other side of the planet. We believe there is a need for an open platform, plus an open ecosystem of partnered vendors to surround that platform.
What is an open platform and how does it deal with the challenges around data access and transfer?
A pre-requisite to maximizing data is to make it both liquid and actionable, and a fundamental step to achieving that is to re-platform scientific data to the cloud, once it’s centralized to a standardized data format. That’s when scientists can start to ask new, deeper questions of the data and take advantage of data visualization and artificial intelligence/machine learning capabilities. So you can now start to compare results that are generated across different systems, different analytical testing modalities and even compare results that are generated from different laboratories or organizations to gain some deep insights.
What does a network of vendors look like and how does it benefit industry and vendors?
The industry is constantly curious and looking to do more with the data, and that’s driving significant partnering by large, small and emerging pharma with the Tetra Partner Network to make their scientific data liquid and actionable. They’re even suggesting other vendors that they would like to see join the network. These three-way collaborations have the potential to accelerate companies’ goals to achieve their desired scientific endpoints.
From a vendor perspective, for some there is a need to adopt new cloud-based technologies and business models to respond to those rapidly changing customer requirements. For some vendors that can be time consuming, even to some of the largest, most strategic vendors in the industry. If you're not cloud-native, it might require assembling new skills and experiences within the organization and that can take time — to adapt and deploy. Conversely, there can be challenges for some of the newer companies that may be cloud-native and have the technologies that can respond to the changing requirements of the industry to collaborate and share the data, but who might be struggling to create market awareness of their offerings and capabilities. In both cases, an open ecosystem of partners can provide value to those companies. So, for some vendors joining an open partnership might provide an accelerated path to accessing cloud-based technologies that can support their capabilities, while for some growth-stage companies joining in a partnership may offer market awareness and market penetration.
Are there concerns from pharma companies when it comes to using an open platform? For example, are they concerned their data might not be safe?
Their scientific data is of the utmost importance to them, there's no question. But we are seeing significant re-platforming of scientific data to the cloud within pharma R&D functions. We’re also seeing a need to maximize scientific data across the full pharma value chain, even within manufacturing and quality. While the rate of adoption in those regulated parts of the value chain may take place at a slower rate, there’s growing interest. One area where there is particular interest is to streamline the engagement and interaction between pharma sponsor companies and contract organizations. Those relationships depend, to a large extent, on the effective and efficient transfer of data between those two entities. Ultimately, the data belongs to the pharma company and they will treat it as they deem appropriate
