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Stay up to date with the latest news from Techspert, and read updates and insights from the many industries we work in

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Techspert's Milestone Achievement in the Financial Times 1000 List

Techspert's recognition as the 539th placement in the Financial Times 1000: Europe’s Fastest Growing Companies underscores our commitment to revolutionizing how expert insights are accessed and applied in the healthcare and life sciences sectors....

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Latest Posts

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Market Trends, Access & Sizing

Why Big‑Pharma’s Direct‑to‑Consumer Pivot Belongs on Your 2026 Checklist

Drug makers such as Roche, Lilly, and Novo Nordisk are starting to sell medicines straight to U.S. patients. If pharmacy benefit managers (PBMs) lose their middle‑man role, every forecast that still assumes a big rebate line could be wrong overnight, and your 2026 strategy could already be outdated.

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Healthcare and Life Sciences
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Market Trends, Access & Sizing

Top 5 Use Cases for Using Expert Networks in Healthcare and Life Sciences

Introduction Expert networks were once used almost exclusively by investors. Today, they’re a critical tool for pharma companies, biotech firms, consultancies and agencies. They enable organizations to make informed decisions - faster - by providing direct access to professionals with deep subject-matter expertise. Whether you’re launching a new therapy, adapting to policy changes, or validating a new campaign, expert calls can provide fresh perspective, reduce risk, and drive better outcomes. These five use cases show how expert networks help solve common challenges: time-sensitive decisions, hard-to-find insights, regulatory uncertainty, and the need for idea validation.

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Compliance & Best Practices

How to Prevent Fraud in Expert Calls: Practical Tips for Recruiters and Researchers

Why You Should Care About Fraud in Market Research Fraud in qualitative research can seriously compromise data integrity and lead to poor decisions being made. Whether it's experts overstating their experience, submitting multiple screeners under aliases, or relying on generative AI during interviews - spotting fraud early is essential to protect research quality.

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