24 Dec
How can the Pharma Industry leverage AI-powered KMS to enhance their research process?
The onslaught of the digital age has been both a boon and bane for the pharmaceutical industry. While the internet has made available a plethora of information and research at the users’ fingertips, there is a lot more data, mostly unstructured, that needs to be stored, found, managed, accessed, and shared. 80% of data generated worldwide is unstructured and exists in different formats (PDF, images, audio, etc.) in siloed apps, making it highly challenging to tap the potential of this data.
Pharmaceutical and biotech companies largely depend on complex research and development (R&D) processes and the specialized knowledge of their staff. Therefore, in such organizations, the risk of losing intellectual capital is significantly higher as technical staff may retire or leave for other opportunities.
Consequently, the pharma industry has been mainly turning to knowledge management systems (KMS) to overcome these challenges, maintain critical data in a more organized manner, and share information between different parts of an organization and with partnering companies in case of acquisitions, mergers, and licensing deals.
Market Research Future’s study, “Global Pharma Knowledge Management Software Market,” reveals that the global pharma knowledge management software market is expected to grow at USD 2 Billion by 2023, at ~17% of CAGR between 2017 and 2023.”
So, what is knowledge management? How can the Pharma industry leverage an AI-powered knowledge management system (KMS) to enhance its research process?
Let’s explore.
How can the Pharma industry leverage AI-powered KMS
Before delving deeper into the role of AI-powered KMS in enhancing pharmaceutical research, let’s first understand what knowledge management is.
Knowledge management is the ability of an organization to capitalize and benefit from the experience, skills, and expertise of its people, as well as retain, document, and transfer this information and other external data.
Challenges in knowledge management faced by the Pharma industry
- Tonnes of unstructured data (clinical trial and drug development) stored in siloed apps that must be carefully maintained
- The risk of losing intellectual capital is significantly high as technical staff retire or leave.
- Need for cross-department sharing of knowledge and transfer of information in case of a merger
- Difficulty in finding patterns and discovering the value of unstructured clinical and pharmaceutical data
- Difficulty in systematically recording feedback collected by sales representatives in the field
Pharmaceutical companies need to carefully document their research and supporting material to replicate past successes and learn from failures. Therefore, pharma enterprises must store and transfer the knowledge from R&D and manufacturing professionals and foster sharing of ideas, data, and experience among colleagues.
Hence, a robust pharma knowledge management system must include document management systems and collaborative digital workspaces that help teams disseminate knowledge and exchange ideas.
Moreover, pharma organizations have a hard time exploring the tonnes of unstructured data stored within their systems. According to Mckinsey, “On average, employees spend 1.8 hours every day and approximately 9.3 hours per week searching and gathering information.”
A knowledge management system must leverage advanced technologies like artificial intelligence (AI) to illuminate hidden data and make it easy for researchers to quickly search for information and find the most incredibly accurate results.
Pharma research and drug development are complex processes, requiring multiple clinical trials on thousands of patients globally. Machine learning technology can help the system recognize unusual patterns in the myriad of clinical trial data and ensure critical life-saving information isn’t overlooked.
Additionally, powerful knowledge management helps salespersons have meaningful interactions with physicians and provide accurate information about drugs. Most importantly, sales reps can collect and store the feedback and data accessed from physicians, which form the basis of future research, manufacturing, and drug development.
Unlock the value of pharmaceutical research with Mesh 3.0’s AI-powered Knowledge Management System (KMS)
At Acuvate, we help clients in the pharma industry improve knowledge management and enhance their research process with our autonomous SharePoint intranet solution called Mesh 3.0.
Mesh provides AI-powered knowledge mining tools driven by Microsoft’s Azure Cognitive Services to harness unstructured data, retain valuable research, and transfer knowledge seamlessly.
Mesh offers a unified knowledge management system with powerful capabilities that “lets information find you.” Here are some of the powerful features of our AI-enabled KMS.
1. Get all your research in one place with flexible app integrations
Build a central repository of all your knowledge, research, and data, structured or unstructured, stored across apps in one place with flexible integrations with Office 365, CRM, ERP, and LoB systems .
2. Tap the value in unstructured data with AI-driven knowledge mining
Hoover estimates the average cost of manually tagging one item between $4 to $7. IDC estimates that it costs $180 to recreate a document that isn’t labeled correctly and can’t be found. Our KMS leverages AI to enable effective knowledge mining, analyze unstructured data, automate content tagging, generate metadata, and find patterns in the plethora of information to help understand data better.
3. Discover information without searching for it by integrating with VIVA Topics
As a Microsoft Gold Partner, we integrate with VIVA Topics to automatically analyze, process, and organize content into Topic cards. VIVA Topics compiles all information related to a particular subject, including a brief description, sites, files, videos, learning resources, and other related pages. When users encounter an unfamiliar word or phrase, they may hover the mouse over it to discover related topic cards.
4. Improve information discoverability with cognitive enterprise search
Our KMS boasts a cognitive enterprise search engine that delivers personalized search experiences. Features like intelligent recommendations, multimedia search, multilingual search, expertise finder, and conversational search help find meaningful information quickly.
5. Share knowledge with social collaboration tools
Mesh 3.0 hosts social capabilities such as enterprise messaging apps (Teams, Slack, etc.), discussion groups, communities and channels, activity streams, and conversations – allowing the one-click share of documents, files, and knowledge.
6. Access information quickly at your fingertips with knowledge bots
AI-enabled bots help pharma personnel access information, documents, and resources on the go via conversational interfaces and natural language interactions.
Finding and sharing information faster with an AI-powered KMS helps enhance the research process, drive collaboration, improve employee engagement, increase employee productivity, and save costs.
To know more about Mesh 3.0 and our AI-powered KMS, please feel free to schedule a personalized consultation and request a free demo.
Poonam Chug is AVP - SaaS Strategy & Business. She has worked in various areas, right from designing and executing sales & account management strategies to reengineering digital workplace solutions. With her determined focus on our mission and progressive approach, she has achieved customer delight in the space of AI, Knowledge Mining, Content & Collaboration, Virtual Assistants, RPA and more. Backed with a deep understanding of customer needs and technology, she leads the SaaS business unit with an upshot of maximizing revenue while ensuring customer satisfaction.
Poonam Chug