2025-09-10

Artificial intelligence (AI) is transforming regulatory compliance in pharma by making it faster, more proactive, and less error-prone. In this interview, Anirudh Ramachandra, Enterprise Sales Consultant at Findability Sciences, discusses how organisations can move from reactive to proactive compliance. He explains how advanced tools like document intelligence, traceability engines, and compliance co-pilots are reducing risk, improving auditability, and driving faster, smarter decision-making in highly regulated environments.

Q. How is AI helping pharmaceutical companies stay ahead in regulatory compliance?

Traditional compliance practices in the pharmaceutical industry present significant challenges - they're resource-intensive, time-consuming, and typically reactive in nature. Companies struggle with constantly changing regulatory requirements that vary across different geographies, creating an incredibly complex landscape to navigate.

At Findability Sciences, we saw an opportunity to transform this through AI. Our approach leverages the use of Natural Language Processing to continuously scan, extract, and summarise evolving regulations from global agencies like the FDA. For a client of ours, we have developed a 510K drafting tool that helps them by saving time during their application process for their new medical devices. We have gotten very good feedback from them since it's gone live and has saved not only man hours but also dollars for them.

Automation extends to repetitive tasks. Through rule-based engines and cognitive automation, we handle data validation, checklist reviews, and document formatting, which significantly reduces human error. Perhaps most importantly, our AI ensures unified interpretation of regulatory guidelines across all departments – R&D, manufacturing, quality, and regulatory affairs teams are all working from the same understanding.

The result is a compliance system that's not only faster and more intelligent, but also significantly less prone to the costly mistakes that have traditionally tormented pharmaceutical compliance processes.

Q. What impact do AI-driven audits have on improving traceability and reducing human error in pharmaceutical processes?

Audit readiness has become a critical pain point for pharmaceutical companies, particularly as regulators are demanding much higher levels of traceability and data integrity. What AI can do is fundamentally transform how audits work - moving them from these periodic, stressful exercises to continuous, real-time processes.

We can integrate AI systems directly with existing data systems like an MES or an ERP platform to create what we can call a 'full digital thread.' This captures and builds a trial of every single material movement, test result or any decisions or feedback throughout the entire process. This would provide comprehensive visibility.

AI models can also be trained on historical audit data, which allows them to detect inconsistencies, missing information, or quality risks long before an actual audit takes place. Think of it as having an internal auditor that actively catches issues proactively rather than reactively.

This approach would improve audit success rates, but also would help organisations build self-correcting systems. Companies move from being audit-reactive to audit-ready.

Q. How can AI-powered RegTech solutions help pharma companies align more effectively with global regulatory standards?

One of the biggest challenges faced by global pharmaceutical operations today is maintaining compliance across incredibly diverse regulatory markets. Each market has its own requirements, and they're constantly evolving - this really impacts accessing new and operational efficiency.

AI-powered RegTech solutions are specifically designed to address this challenge. The systems can continuously scan databases and repositories for updates in legislation, guidance documents, and compliance protocols. The advantage of this approach is that we can process documents in multiple languages using Natural Language Processing, so we're not missing critical updates regardless of their origin.

Custom dashboards can be built that provide compliance visibility across all functions and regions. This gives insight to companies prioritising resources and allocating them where they're needed most. 

The result is that pharmaceutical firms can remain synchronized with international requirements in real-time. This would essentially eliminate the traditional lag between regulatory changes and organizational adaptation, which would significantly reduce the risk of compliance lapses and, critically, market entry delays that can cost companies millions.

Q. In what specific ways is AI accelerating the drug development lifecycle—from laboratory research to market launch?

Starting with the discovery phase, AI models can analyse vast chemical, genomic, and biological datasets to identify viable drug targets and promising compounds. Using deep learning techniques to simulate molecular interactions and prioritise compounds for further testing, which dramatically accelerates what has traditionally been a very time-consuming selection process. This is actually something we do for a drug manufacturing client based in the US, where we are helping them in their drug discovery process by reading fast files on different amino acids, protein molecules, and other Biomolecules.

Moving into preclinical and clinical trials, AI can revolutionize patient recruitment by mining data from electronic health records, social media, and clinical registries to identify suitable candidates much more efficiently.  AI also optimises trial protocols through simulations based on historical outcomes and continuously monitors ongoing trials for protocol deviations and the occurrence of adverse events in real-time.

During the regulatory submission phase - which is often a major bottleneck – Findability’s AI automates the extraction and formatting of data into submission-ready formats. It cross-references everything against global regulatory guidelines to ensure accuracy and completeness, which significantly reduces the back-and-forth that typically happens with regulatory agencies.

But why stop there. Post-market, AI analyzes unstructured data from call centers, social platforms, and health records to detect adverse events early, often before they become widespread issues.

This end-to-end integration allows pharmaceutical companies to reduce development timelines, improve trial efficiency, and ultimately ensure safer, faster product launches. We're essentially compressing what used to be a 10-15-year process while actually improving quality and safety.

Q. How does Findability Sciences ensure governance, transparency, and accuracy in AI deployment within regulated sectors like healthcare and pharma?

At Findability Sciences, we've developed a comprehensive approach to AI governance that prioritizes trust, accountability, and transparency at every level.

First and foremost, our models are built with explainability as a core requirement, not an afterthought. This is crucial because in pharma, you can't just have a black box making critical decisions - stakeholders need to understand why the AI reached a particular conclusion.

We've implemented stringent version control that captures model lineage, input sources, and decision logs for every single AI-driven outcome. These comprehensive records aren't just for internal oversight - they're critical when external regulatory audits happen, and auditors need to trace back through our decision-making process.

Our platforms comply with AI ethics standards by maintaining complete transparency in training data sources and incorporating bias detection mechanisms. We also use human-in-the-loop systems where expert validation is necessary - because while AI can process information incredibly efficiently, human judgment remains essential for critical decisions.

These safeguards collectively create a framework where AI can be trusted to perform consistently and ethically, even in the high-risk, highly scrutinized pharmaceutical environment. It's about building confidence not just in the technology, but in the entire governance structure surrounding it."

Q. How is AI transforming legal workflows to enhance regulatory compliance, risk management, and real-time policy adherence across industries?

Legal and compliance departments are really at a breaking point right now. They're being asked to manage exponentially more regulatory complexity while maintaining oversight of policy adherence across their organisations. The traditional approach of manually reviewing documents and reactively responding to regulatory changes just isn't sustainable anymore.

What we've built at Findability Sciences is essentially an AI-powered nervous system for legal operations. Our natural language processing technology can digest massive volumes of legal documents – contracts, agreements, regulatory filings – and automatically identify the critical elements that matter most. We're talking about extracting key clauses, flagging missing provisions, and catching inconsistencies that might take human reviewers days or weeks to discover.

But document review is just the beginning. We've also created an AI engine that constantly monitors regulatory databases, tracking court decisions, and scanning government notices 24/7. When there's a legislative change or new ruling that could impact our clients' compliance obligations, they get immediate alerts. This transforms legal teams from being reactive to being proactive.

With AI you can maintain a comprehensive repository of regulatory policies and continuously compare actual business activities against these standards. The moment there's a deviation – whether it's a contract clause that doesn't align with current regulations or a business process that's drifting from compliance standards – the system flags it instantly and suggests corrective actions.

For legal risk management, we have developed machine learning models that analyze multiple risk factors simultaneously – contract values, jurisdictional complexities, historical dispute patterns, the reliability track record of counterparties – to generate quantified risk scores. Legal teams can now make data-driven decisions about where to focus their attention and resources. For a large Insurance company based in Canada, we have developed an agentic workflow engine that helps them validate internal risks and generate reports, and provides feedback on how the risk can be mitigated. This system has now become an integral part of their process to eliminate any liability and also be audit-ready.

The transformation we're seeing with our clients is remarkable. They're moving from a reactive, overwhelmed legal function to one that's predictive, responsive, and strategically aligned with business objectives. They're reducing regulatory risk while enabling greater business agility – which is exactly what modern enterprises need to stay competitive.

Q. What tangible ROI can pharma companies expect from integrating AI into their compliance and regulatory workflows?

We have concrete, measurable results that demonstrate AI's impact on the bottom line in the pharma industry.

Our pharmaceutical clients are seeing dramatic improvements in compliance cycle times. We're talking about 30 to 50 percent reductions in the time it takes to complete compliance processes. This happens because we're automating the most time-intensive parts of documentation, validation, and review workflows that traditionally required weeks or months of manual effort.

The audit story is even more compelling. Manual audit efforts have decreased by up to 70 percent using AI. Think about what that means – instead of teams spending weeks pulling together data, checking for inconsistencies, and compiling evidence, AI systems handle these data-intensive tasks automatically. That's not just cost savings; that's freeing up your most skilled professionals to focus on strategic work that actually moves the business forward.

From a revenue perspective: faster, more accurate regulatory submissions directly translate to shorter approval timelines. In pharmaceuticals, everyday matters when you're trying to get a product to market. AI helps companies submit cleaner, more complete regulatory packages, which means fewer back-and-forth cycles with regulatory agencies and faster time to market. That acceleration directly impacts revenue generation.

We're also seeing significant risk mitigation benefits. Proactive compliance monitoring dramatically reduces the likelihood of penalties, recalls, and regulatory actions. When you consider that a single recall can cost millions in direct expenses plus immeasurable brand damage, the risk reduction value becomes enormous.

What I find most strategic is how this technology transforms human capital allocation. Instead of having PhD-level scientists and regulatory experts doing repetitive documentation tasks, they're now focused on innovation, strategic planning, and complex problem-solving – activities that actually drive competitive advantage.

The ROI story here isn't just about cost savings, though those are substantial. It's about speed to market, risk reduction, operational excellence, and fundamentally transforming how your most valuable people spend their time. That's the kind of strategic impact that defines market leaders.

 Q. What are Findability Sciences' offerings for Pharma manufacturing companies? 

We've established strong partnerships with several major pharmaceutical companies, supporting them throughout the entire drug development lifecycle. Our engagement begins at the earliest stages with drug discovery, where we analyze large datasets and help evaluate different interaction approaches between proteins and other biomolecules.

Our expertise extends beyond discovery into regulatory compliance. We've developed a comprehensive 510(k) automation tool for a major Canadian medical device manufacturer, streamlining their FDA submission process significantly.

Currently, we're developing an innovative backend marketing copilot designed specifically for internal sales and marketing teams. This tool will provide data-driven insights to help teams identify optimal cross-selling and upselling opportunities with precision.

We maintain ongoing relationships with pharmaceutical industry leaders, continuously implementing process automation solutions that deliver measurable time and cost savings. Our focus remains on identifying areas where technology can eliminate inefficiencies and accelerate critical business processes in the life sciences sector.