04 May 2026
Explains how clinical trial intelligence is reducing manual landscape analysis in drug development, improving speed, consistency, and planning decisions.
Pharma competitive intelligence04 May 2026
Explains how pharma teams are shifting from quarterly reports to real-time signals for competitive intelligence, improving visibility and faster decision-making.
AI authoring platform04 May 2026
Explains how AI authoring platforms help create living, traceable regulatory submissions in life sciences, supporting consistency, updates, and compliance.
enterprise AI platform29 Apr 2026
An enterprise AI platform enables organizations to build, deploy, and manage AI solutions at scale. Learn how to evaluate trusted, explainable AI systems that meet compliance and transparency requirements in regulated industries.
KnolPersona31 Mar 2026
The EU Joint Clinical Assessment (JCA) regulation became mandatory for these product classes, creating a single EU-level clinical assessment that runs in parallel with the EMA regulatory review, not after it. For pharma teams accustomed to beginning HTA dossier preparation following regulatory approval, this is a strategic and operational discontinuity of the first order.
competitive intelligence29 Mar 2026
In the pharmaceutical industry, where a single competitor's Phase III readout can reshape a multi-billion dollar market overnight, the difference between knowing first and knowing last is not a matter of competitive preference. It is a matter of commercial survival.
AI for drug development27 Mar 2026
For years, AI adoption in drug development has outpaced the regulatory frameworks governing it, leaving sponsors to build AI-powered trial design capabilities on data infrastructure that no agency had formally evaluated.
KnolForge27 Mar 2026
Most pharma organisations in 2026 are not short of AI tools. They have one platform for literature search, another for regulatory writing, a third for competitive monitoring, a standalone modelling tool for health economics, and a generic large language model that teams use informally for drafting and summarisation. Each tool solved a problem at the point of purchase. Together, they have created a new problem: fragmented intelligence, broken audit trails, and compounding governance risk.
KnolAI25 Mar 2026
Consider this scenario: an advisory board meeting is scheduled in three weeks. A payer wants a rapid-turnaround evidence summary on your asset's comparative effectiveness versus the current standard of care. Your HEOR team is still three weeks deep into a manual literature review that will not be complete for another month.
KnolAi23 Mar 2026
Any Transformational change in the pharmaceutical research field often starts with the realisation that the industry’s evidentiary foundation is inherently fragmented.
AI for drug development18 Mar 2026
The structural transformation in clinical trial development began with a tool so routine that its constraints went unquestioned.
AI Software for Healthcare11 Mar 2026
For the better part of a century, the assumption has been this: proprietary data is a competitive advantage, and competitive advantage is never shared.
clinical trial design software04 Mar 2026
Every transformative shift in clinical trial design begins with a question that challenges an assumption so embedded that it is rarely examined. For decades, that assumption has been this: every trial needs a live placebo group.
systematic literature review29 Jan 2026
In the complex landscape of Health Economics and Outcomes Research (HEOR) and Market Access, the systematic literature review is the bedrock of evidence.
KnolScapes27 Jan 2026
In the pharmaceutical industry, the only certainty is uncertainty. Yet, decisions involving billions of dollars and years of development are often made based on linear assumptions that fail to account for the dynamic reality of the market.
AI in healthcare24 Jan 2026
Artificial intelligence is no longer a futuristic concept; it is an operational reality. However, the deployment of AI in life sciences faces a unique hurdle that consumer tech does not: the zero-error mandate. When a recommendation engine suggests the wrong movie, it’s an annoyance.
AI for drug development22 Jan 2026
In the high-stakes world of drug development, timing is everything. Traditionally, teams have treated pharmaceutical competitive intelligence as a monitoring function, something to look at once a study is underway or nearing commercialisation.
AI for drug development21 Jan 2026
The pharmaceutical landscape in 2026 is defined by a paradox: we have more data than ever before, yet the path to a successful approved therapy remains fraught with costly delays.
KnolScape19 Jan 2026
People love to compare drug development to a marathon. It sounds noble, right? The long haul, the endurance, the solitary push.
Knolens SLR16 Jan 2026
In the high-stakes poker game of drug development, playing your hand without watching the other players isn’t bold, it’s reckless.
Knolens SLR14 Jan 2026
The pharmaceutical industry has never stood still, but today, the pace of innovation and competition is redefining how clinical strategy must operate. The days of developing a drug in isolation, confident that the sheer science would secure market dominance, are long gone.
KnolAI10 Jan 2026
Clinical development teams spend 40+ hours per month manually extracting competitor trial data, time that could be spent on strategic planning. Yet 62% of protocol amendments stem from avoidable competitive blind spots identified too late.
KnolScape08 Jan 2026
Protocol amendments cost pharma companies $535K on average and delay trials by 6+ months. Yet 40% of amendments stem from avoidable design flaws that benchmarking could have caught.
Pienomial29 Dec 2025
The pharmaceutical and life sciences sector is in a huge transition. You can't deny the efficiency AI offers, but here’s the sticking point: unlike most other industries, pharma can’t afford to rush. Every bit of evidence produced from trial data to value dossiers must survive intense scrutiny from regulators, HTA agencies, and global payers. So, the future isn't just about deploying AI; it's about being strategic and adopting truly compliant AI in healthcare.
systematic literature review28 Dec 2025
The pharma industry sits right at the intersection of breakthrough science and ironclad regulation. There’s practically zero room for error. AI promises to turbocharge drug discovery, speed up clinical trials, and simplify those exhausting regulatory submissions. But here’s the thing: there's a huge chasm between general-purpose AI and the truly reliable AI for life sciences needed for GxP environments.
Pienomial27 Dec 2025
The pharmaceutical industry has a timing problem. We spend years developing a molecule. We spend months designing a clinical trial. We spend weeks compiling a systematic literature review. But the market does not wait for our timeline.
Knolens SLR26 Dec 2025
We are living through a data paradox. We have access to more clinical information than at any point in human history, yet the ability to verify that information has never been more fragile.
Pienomial25 Dec 2025
The life sciences sector produces huge volumes of clinical, regulatory and scientific data. Most organisations find themselves struggling because their evidence lives in separate tools, databases, and team environments.
Pienomial24 Dec 2025
Market Access teams work in rapidly evolving environments where payer demands, clinical changes and competition change rapidly. To build compelling value stories, teams must act as soon as information reaches them.
KnolAI23 Dec 2025
Healthcare and life sciences are producing scientific information at an unprecedented pace. Every year, millions of new publications emerge across clinical trials, real‑world studies, regulatory decisions, conference abstracts, and health economics research.
Knolens SLR22 Dec 2025
Health technology assessments, regulatory submissions, and evidence-based decision frameworks depend on comprehensive and systematically evaluated scientific literature.
KnolScapes18 Dec 2025
The field of drug development is entering a new era characterised by data-driven decision-making, predictive modelling and advanced computational science. Over the last 20 years, costs to bring a new therapy to market have increased by close to a tenfold increase, typically referred to as Eroom’s Law.
Systematic Literature Reviews15 Dec 2025
In the modern life sciences landscape, data is no longer the bottleneck; the bottleneck is synthesis. Pharmaceutical companies, specifically Health Economics and Outcomes Research (HEOR)
