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Als CRO unterstützt das medXteam Sie während des gesamten Prozesses der Generierung und Bewertung klinischer Daten und bei der Zulassung und Marktbeobachtung von Medizinprodukten

11/05/2026

📄 From abstract to decision – how structured extraction speeds up your screening process

Abstract screening is where cognitive fatigue sets in fastest.

You're reading dense, inconsistently structured paragraphs – each one containing the information you need to make an inclusion decision, but rarely presented in the same way twice.
After 50 abstracts, concentration drops. After 150, inconsistency creeps in.

The solution isn't to screen faster. It's to screen smarter.
Structured extraction means pulling the same key elements from every abstract – regardless of how the original is written:
✔ Study design – RCT, observational, registry, case series?
✔ Patient population – Who was studied? How many? What indication?
✔ Device or intervention – Is this truly comparable to your device?
✔ Primary endpoints – What was the study designed to measure?
✔ Key outcomes – What were the results?

When this information is presented consistently across all abstracts – whether extracted manually, with a template, or with AI support – reviewers work faster, make better decisions, and produce a more defensible screening log.
Whether you use AI to generate this structure or build it manually into your screening template – the principle is the same: consistency drives quality.

08/05/2026

🤖 Where AI genuinely helps in literature screening – and where it doesn't

AI tools are increasingly part of how clinical evaluation teams work.

Where AI adds real value:
✔ Title screening – AI can flag potentially relevant titles and add brief context notes, significantly speeding up first-pass review
✔ Abstract extraction – Structured extraction of study design, population, endpoints, and outcomes from dense abstracts
✔ Consistency – AI applies the same logic across hundreds of records, reducing variability between reviewers

Where AI has clear limits:
⚠ Critical appraisal – Assessing methodological quality requires clinical judgment that AI cannot reliably provide
⚠ Clinical interpretation – Linking evidence to your specific device and patient population is expert work
⚠ Inclusion decisions – Every final decision must be made and owned by a qualified evaluator
⚠ Hallucination risk – AI can generate plausible-sounding content that isn't in the source – always verify critical data points

The way we think about it: 👉 AI handles preparation. Experts handle judgment.
That distinction isn't just good practice – human oversight at every critical step is non-negotiable.

06/05/2026

⚡ Many search results, one deadline – how to approach high-volume screening without losing quality

You've built a solid search strategy. You've run the search across all relevant databases.
And now you're looking at 100 - 1,000 results. Maybe more.

Let's put this in perspective: Screening 1,000 abstracts at just 2 minutes each = over 33 hours of work – before full-text review even begins.
Under the MDR, this process must be systematic, transparent, and reproducible. There is no shortcut around that requirement.

This is the moment where many clinical evaluation projects slow down – or where shortcuts start to creep in.

The challenge is real: screening needs to be systematic, transparent, and reproducible under the MDR. But it also needs to happen within a project timeline that doesn't allow for weeks of manual review.

How do you maintain quality at volume?

Start with a clear screening protocol
Before you screen a single title, document your inclusion and exclusion criteria. These must be defined upfront – not adjusted as you go.

Work in stages
Title screening → Abstract screening → Full-text review. Each stage reduces volume before the next begins. Don't jump to full-text review without completing earlier stages properly.

Use a structured screening log
Every decision needs to be traceable. Who screened it, what decision was made, why a paper was excluded. This is your audit trail.

Consider where AI tools can support
At title and abstract level, AI can help structure and accelerate the process – reducing cognitive load without removing human judgment. More on this in upcoming posts.

Build in a quality check
Have a second reviewer check a sample of exclusion decisions, especially at title level. Catch inconsistencies early.
The goal isn't just speed. It's a screening process that you can fully defend – at every step, for every decision.

04/05/2026

📋 The literature process in clinical evaluation – why most teams start in the wrong place

Here's a scenario we see regularly:
A manufacturer starts their CER process by running a literature search. Hundreds of results come in. Screening begins. Weeks pass.
And then – halfway through – it becomes clear that the search wasn't aligned with the clinical evaluation plan. Or there isn't one yet.
The result: time lost, work repeated, deadlines missed.
The most common mistake in clinical evaluation isn't poor ex*****on. It's starting in the wrong place.

A compliant, efficient literature process follows a clear sequence:
1️⃣ Clinical Evaluation Plan (CEP) Define scope, intended purpose, target population, and clinical parameters before anything else.
2️⃣ Search Strategy Build your search based on the CEP – databases, search terms, inclusion/exclusion criteria.
3️⃣ Literature Search Execute systematically and document every step.
4️⃣ Screening Title, abstract, and full-text review against pre-defined criteria.
5️⃣ Critical Appraisal Assess methodology, quality, and clinical relevance of included studies.
6️⃣ CER Synthesize the evidence into a compliant clinical evaluation report.

Each step depends on the one before it. Skip or rush any stage – and the whole process becomes harder to defend.

Over the next few weeks, we'll walk through each of these steps in detail – with practical tips and common mistakes.

29/04/2026

🎙️ New Podcast Episode is Live!

Clinical evaluation without pitfalls — the practice-oriented checklist for MDR

Clinical evaluation under the MDR is not just a one-time task — it’s a continuous, strategic process that determines the safety, performance, and clinical benefit of your medical device throughout its entire lifecycle.

In this episode, we break down the key elements of a robust, audit-proof clinical evaluation:
🔍 How to define a precise intended purpose as the foundation for your entire evidence strategy
🗺️ Why a solid Clinical Evaluation Plan (CEP) is your roadmap — not an afterthought
⚖️ How to choose the right evidence route (clinical data, equivalence, or Article 61(10))
📚 Best practices for a systematic and reproducible literature search
🎯 How to formulate measurable, traceable clinical claims
🔄 Why PMS & PMCF are essential to keep your CER alive
📈 How to manage the CER lifecycle and stay inspection-ready

Whether you're preparing a new Clinical Evaluation Report (CER) or optimizing your existing process, this episode gives you a clear, hands-on framework to avoid common pitfalls and strengthen your documentation.

🎧 Listen now:
https://open.spotify.com/episode/5dR358R3JjYp8XyNU1FYOL?si=0jQANFA6RwGfXdXWDKSCmQ
https://podcasts.apple.com/de/podcast/medxteam-kompakt/id1710726795?i=1000764252024

27/04/2026

🚨 EUDAMED Becomes Mandatory on 28 May 2026 — Are You Ready?
The transition period is ending.
On 28 May 2026, EUDAMED becomes fully mandatory❗️
💡The following modules will no longer be optional:
✔️ Actor registration
✔️ UDI/device registration
✔️ Notified Bodies and Certificates
✔️ Market Surveillance.

💡The European Commission has published an updated roadmap outlining the implementation timeline and transition details
Recent Timeline:
https://health.ec.europa.eu/document/download/04ce2012-97df-4dd0-8a39-d4f6993b9e16_en?filename=md_eudamed_roadmap_en.pdf
📚Training material:
https://webgate.ec.europa.eu/eudamed-help/en/welcome-to-the-eudamed-information-centre.html

Are you already operating as if EUDAMED were mandatory — or are you still in “voluntary mode”?

24/04/2026

How to Handle Conflicting Study Results

What happens when studies do not comply with the CER?
Conflicting evidence is common in clinical research.

Step 1: Assess Methodological Quality
Not all studies carry equal weight.
Consider:
✔️ Study design
✔️ Sample size
✔️ Follow-up duration
✔️ Endpoint definition
✔️ Risk of bias
Higher-quality evidence may reasonably outweigh weaker data.

Step 2: Analyze Population & Endpoint Differences
Conflicts often arise because:
✔️ Different patient populations were evaluated
✔️ Different endpoints were used
✔️ Follow-up duration varied
Understanding context reduces apparent contradiction.

Ignoring conflicting data weakens credibility.
Addressing it strengthens defensibility.

💡 Need support with clinical investigations, clinical evaluation or post-market activities?
👉 Learn more at https://www.medxteam.de/en/services/clinical-evaluations

22/04/2026

Search String Engineering – Why Keywords Alone Are Not Enough

A literature search is not a list of keywords.
It is a structured query strategy.
Poorly constructed search strings can miss relevant studies — or generate thousands of irrelevant hits.

Effective search string engineering includes:
✔️ Boolean operators (AND, OR, NOT)
✔️ Controlled terms and wording
✔️ Free-text synonyms
✔️ Field tags (title, abstract, full text,...)

The Risk of Keyword-Only Searches
🚩 Missing synonyms
🚩 Ignoring controlled indexing
🚩 Overly narrow combinations
🚩 Uncontrolled explosion of irrelevant hits
For example:
Searching only
“cardiac device complications”
may miss studies indexed under different terminology.

💡 Need support with clinical investigations, clinical evaluation or post-market activities?
👉 Learn more at https://www.medxteam.de/en/services/clinical-evaluations

17/04/2026

Updating Your Literature Search

Clinical evidence does not stand still — and neither should your search.

When Should You Update Your Literature Search?
Updates should be:
✔️ Periodic (Risk-Based)
-Higher-risk devices require more frequent updates
-Class III and implantable devices are typically reviewed annually
-Lower classes follow risk-justified intervals
✔️ Trigger-Based
-New PMS findings
-Safety alerts
-Significant PMCF findings
-Changes to intended purpose or claims

If literature is only updated “before the audit,” the system is reactive — not compliant.

💡 Need support with clinical investigations, clinical evaluation or post-market activities?
👉 Learn more at https://www.medxteam.de/en/services/clinical-evaluations

16/04/2026

💡 New Blog Post Online: Literature Review for Clinical Evaluation – Best Practices

A robust literature review is not just a formality under the MDR — it is the foundation of your entire clinical evaluation.
In our latest blog post, we break down how to turn your literature search into a systematic, transparent, and audit-proof process.

👉 What you’ll learn:
How to develop a clear and reproducible search strategy
How to define structured inclusion & exclusion criteria
How to avoid bias during study selection and screening
How to critically appraise and translate evidence into clinical claims

📖 Read the full article now: https://www.medxteam.de/en/medxteam-blog/literature-review-for-clinical-evaluation-of-best-practices

15/04/2026

When Literature Is Not Enough
🔍Recognizing data gaps is a strength — not a weakness.

A comprehensive literature search is essential for Clinical Evaluation.
But sometimes, even a well-executed review reveals one uncomfortable truth:
The available evidence is insufficient.

Typical Situations Where Literature Falls Short
✔️ Small sample sizes
✔️ Non-comparable patient populations
✔️ Conflicting outcome results
✔️ Limited data for specific subgroups or indications

What Happens Next?
Literature gaps should directly inform:
✔️ PMCF planning
✔️ Claim adjustments
✔️ Potential need for clinical investigation

💡 Need support with clinical investigations, clinical evaluation or post-market activities?
👉 Learn more at https://www.medxteam.de/en/services/clinical-evaluations

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