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Vera K.
CEO @ Atrix AI - Medical Affairs | Cornell, YCombinator
Vera Kutsenko is the Founder and CEO of Atrix AI, a company that helps medical affairs teams transform data into actionable insights to improve patient outcomes.23 She has a strong background in technology and entrepreneurship:
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Education: Vera holds a Bachelor's and Master's degree in Computer Science from Cornell University.2
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Professional Experience:
- Founded Atrix AI, focusing on healthcare and medical affairs.23
- Previously co-founded Neverland, an online home garden and lawn marketplace backed by Y Combinator (W21).12
- Worked as a senior software engineer at Uber, specializing in Android development.24
- Held positions at Facebook as a software engineer and at Goldman Sachs as a tech analyst intern.2
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Entrepreneurial Ventures:
Vera's expertise spans software engineering, artificial intelligence, and entrepreneurship, with a current focus on leveraging AI to improve healthcare outcomes through Atrix AI.35
Highlights
Medical affairs leaders: How do you prove the impact of your field medical team?
Here’s why traditional field medical analysis might be holding you back.
You’ve collected a wealth of qualitative data across field medical, med info, and med education, but how do you ensure it’s truly reflecting your team’s impact and progress of your scientific objectives?
🌟 Let’s walk through a scenario: Imagine you’re focused on educating about 2nd vs. 3rd line therapy uses of your medication this half.
After gathering detailed MSL + med info notes, how can you analyze and be sure that your efforts are making a real difference?
Typically, there are two ways to approach analyzing field notes (+ other data sources) today:
1⃣ AI summarization tools: copilot, chatgpt 2⃣ Keyword tagging using NLP
Here’s where we get with these in measuring impact:
1⃣ AI Summarization Tools: These tools take your field notes and generate summaries. The issue? Their accuracy diminishes with larger datasets, often missing key notes and lacking reliable auditability to verify the summaries. Picture trying to condense 5,000 notes into ChatGPT—good luck with that!
2⃣ Keyword Tagging: NLP systems assign keywords like "second-line-of-therapy" to your notes. But here’s the catch: if you find 100 notes tagged with a term, does that truly measure impact? It only shows conversations about a topic without revealing if these discussions drove meaningful change.
⚠️ Both methods offer a surface-level analysis or "pixelated" view of trends—think of a 1970s video game graphic. They overlook the essential (”HD”) details needed to accurately gauge impact. For instance, among those 100 notes, how many expressed confusion or clarity about therapy guidelines? Traditional tools might miss these critical nuances.
🌟 So, what’s the solution? To truly capture the "HD" view of your impact and grasp the critical nuances, you need to integrate advanced tech tools and techniques from NLP, LLMs, and other AI algorithms. This will ensure you address what traditional methods don't: comprehensiveness, accuracy, and context/nuance.
Here’s how it works:
Step 1: AI Model Analysis -- Each note and data source is examined for relevance.
Step 2: Theme Identification -- The model uncovers detailed themes across all notes.
Step 3: Pattern Clustering -- It groups related themes to identify overarching trends.
Step 4: Data Enrichment -- The model enhances insights with sentiment analysis, tagging, and time tracking.
Step 5: Comprehensive Reporting -- The result is a detailed report that thoroughly breaks down the nuances of 2nd and 3rd line therapy.
Imagine being able to measure the impact of your efforts with this level of detail in just a few minutes. This is not only possible—it’s available today.
If you’re looking to do more to level up your capabilities in measuring the impact of your efforts across field, med info, and medical education — dm me!
How do you know if your medical affairs efforts are moving the needle? Here’s how to track the true impact of your work.
Measuring success in medical affairs isn’t just about tracking surface-level metrics—it’s about understanding the trends and nuances within themes, topics, and key insight questions (KIQs) over time.
But how do you get the full picture?
Part of measuring success in medical affairs efforts across field and med info is tracking the result of your efforts over time.
Imagine you’re monitoring a drug like Perolax, indicated for type 2 diabetes.
You want to track HCP opinions on nausea as a side effect.
Traditionally, you might:
- Manually sift through field notes and med info inquiries for keywords like “nausea.”
- Read through all the notes
- Write up a report, possibly on a quarterly basis.
- Manually compare sentiments across periods.
This approach is time-consuming and often limited to a single channel, which means you could be missing out on a comprehensive view of what’s really happening.
Traditional NLP tools will typically show word clouds or trends over time with specific keywords which can help track changes in keyword mentions over time.
However, keyword tracking lacks the richness to uncover the full story behind theme (nausea in this case).
So, how can you enhance this process today?
Emerging AI technologies can automate and deepen your analysis across multiple channels:
☑️ Smart Tagging: AI can automate the tagging of relevant data points—something we've been able to do, but now with more sophistication.
☑️ Deeper Insights: Generative AI combined with NLP and other qualitative analysis techniques can automatically identify trends and sub-themes in your data with much more granularity.
☑️ Continuous Monitoring: AI keeps track of these trends over time, alerting you to any significant changes or emerging patterns.
By shifting from manual keyword tracking to AI-driven analysis, you gain richer, more actionable insights—giving you a comprehensive understanding of how side effects like nausea might impact patient adherence and strategy.
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Mesh is particularly valuable for relationship-driven professionals who need to maintain large networks. The app is popular among many industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. Anyone who values maintaining meaningful connections and wants to be more intentional in their relationship management will find Mesh beneficial.
Mesh offers competitive pricing in the personal CRM market. Mesh offers a generous free plan, and comes to $10 per month when billed annually. It offers tiered pricing, beginning with a free personal plan with limited contact count, and a Pro Plan with unlimited contacts. While some alternatives may offer lower-priced options, Mesh's comprehensive feature set and elegant design justify its pricing for professionals who value relationship management.
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