In pharmaceutical formulation development, data infrastructure extends beyond formulators, presenting an opportunity to unite them with manufacturers, regulatory teams, legal counsel, finance departments, and other business units. The ultimate goal is to enhance operational efficiency and effectiveness throughout the organization.

However, the reliance on scattered data sources, such as lab notebooks, spreadsheets, and databases, poses significant difficulties in data management and discoverability for pharma organizations. The resulting manual effort required to sift through blocks of text or spreadsheets increases research time, hampers productivity, and leads to duplicated efforts and overspending. Insights and transparency between groups are severely limited, further complicating this issue.

60% of companies experience a project delay or failure due to formulating challenges, with more than half of those delays lasting over 12 months.

By unlocking and structuring dark data across different sources, teams can uncover valuable relationships between data elements for smarter and faster scientific, operations, and business decision-making.

You need clean, connected, and searchable data to identify valuable patterns and streamline pharmaceutical formulation development

You may find the answers to critical questions within your legacy data management methods, which hold procedures, processes, and ingredient information. What happens if you can’t access it to drive decisions?

Without standardization, inconsistencies arise, impeding efficient data retrieval. For instance, a simple ingredient like ethanol may be documented as alcohol or ethyl alcohol across different lab notebooks. This variance hampers searchability and contributes to incomplete information, potentially resulting in ill-informed decisions and costly reformulations.

In a recent CAS survey, formulation scientists admitted to spending 60% of their lab time iterating formulations.

The incredible time burden formulation scientists and IP researchers face during this phase of a company’s pipeline can significantly affect the overall time taken to market a product. By accessing reliable, well-curated information designed for formulation scientists, companies can gain the strategic value of formulation data while increasing efficiency. Data users can reduce the time spent on manual information processing, eliminate unnecessary iterations, and accelerate the formulation workflow.

Unlocking dark data is advantageous for those lacking extensive experience. It enables an accelerated understanding of technology, science, and the compatibility of different elements within formulations. New employees can quickly grasp the intricacies of current pharmaceutical formulation development and prior efforts by tracing data across various phases, considering properties, examining functions, and analyzing common usage.

Learn how to maximize the strategic value of formulations in pharma. Download the White Paper

Structuring information and enabling data connections should go beyond pharmaceutical formulation development teams

As you manage multiple product lines, repurpose drugs and ingredients, and develop novel therapeutics, sharing data becomes essential.

Each phase of a pharmaceutical’s life cycle generates new data. Deploying strategies that unlock dark data, eliminating data silos, and optimizing information structures can help individuals identify patterns and opportunities hidden in information throughout the pharmaceutical life cycle — from patent landscape analysis and raw materials selection to pricing and end-of-product life.

After identifying all the related information, you can gradually establish consistency and a searchable platform for formulations data, regulatory approvals, clinical trial status, materials grade and scale, feedstock pricing, ingredient supplier information, and more. This introduces a new level of transparency and collaboration between development formulators, manufacturing formulators, IP counsel, finance departments, and marketing teams, allowing them to retrieve the information they need efficiently:

• Identify opportunities and risks of active ingredients for drug repurposing or novel therapeutic development based on intellectual property (IP), regulatory, and competitive insights.
• Access formularies related to your active ingredients across disciplines within your organization.
• Source ingredients from stable suppliers or identify supplier alternatives that power development and bulk scale.
• Access market data to identify NAICS codes of customers and tailor the formulations to the highest number of those codes.
• Perform a feedstock analysis and determine a new product's cost and appropriate pricing.
• Research ingredient properties and similar structures and identify all examples of formulations and internal development activities where that particular ingredient was used.

Maximize ROI by building a reliable competitive intelligence mechanism

Full disclosure in the pharma industry means no trade secret environment exists. Patents, clinical trials, and regulatory approvals are highly structured. Pharma companies can use this information to guide internal formulation strategies.

For instance, you can determine if a patent protects a formulation and identify its excipients within the discovery phases. You can trace the data through several phases and information types to determine the formulation, its use and delivery, function, and performance.

Moreover, to avoid gaps in IP knowledge, IP researchers spend additional time on relevant search strategies. To ensure an exhaustive IP search, professionals can spend weeks scouring through hundreds of patent documents to find even simple answers during the formulating phase.

Access to thoroughly indexed, structured competitor data allows you to easily see patterns and identify where you need to or could be competing. Access to quality databases and a structured knowledge management platform allows you to reliably and efficiently get answers to essential questions:

• What are competitors claiming as part of their formulations?
• What example formulations do they have?
• What specialized ingredients are they using?
• Are they using something new?

You can then relate those insights to your organization's data, capabilities, and initiatives to identify potential formulation opportunities.

We have all these disparate databases and we don't know how to future-proof their integration — Where do we start?

Pharmaceutical companies must address siloed data because everything else is becoming structured. The industry continues to progress toward pharma 4.0, and compliance guidelines are evolving.

Think about where you are stuck first. Where do you get frustrated when you're looking for information? What can't you find? What questions are you trying to answer?

Explore why this is a problem and what you are trying to accomplish when this happens. Once you start to have an understanding of your problems and your challenges, then you can begin to productively discuss what you need.

Get to the root of what you need. Then assess the areas of dark data you need to unlock, the maturity of the governance structures for the information sources you need to connect, and the data leaders that will help define the solutions.

Learn how a large health-tech organization addressed decades of key research trapped in “dark data”, costing them considerable time and money.

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Gain an information advantage. Invest in knowledge management solutions that fuel profitable pharmaceutical formulation development

To stay ahead of the competition, pharmaceutical companies need to leverage every aspect of the value chain, especially the formulation phase. Formulations significantly influence patient compliance and impact market success. Companies benefit from providing formulation scientists with relevant research platforms to make workflows more efficient and speed up formulations R&D. Investing in different steps of a formulation scientist’s workflow upgrades the company’s positioning by giving an information advantage over competitors.