GLASGOW, Scotland--(BUSINESS WIRE)--Talking Medicines has today (Thursday 4 February) launched an AI-powered social intelligence service, PatientMetRx, giving the world’s leading drug brands insights on patient experience on a scale and depth never previously possible.
PatientMetRx uses AI to provide a systematic way of measuring patients’ experience of taking medicines.
Powered by EVA, a proprietary AI machine developed by Talking Medicines, PatientMetRx combines Machine Learning and Natural Language Processing to capture the voice of the patient from millions of conversations taking place over multiple sources including social media, forums and blogs, mapped to a curated database of 130,000 regulated global medicines. It distils what patients are saying online and more importantly, what they are feeling, into powerful data insights which are fully pharma compliant.
Delivered on a digital dashboard, PatientMetRx provides pharma marketeers with a Patient Confidence Score to benchmark each medicine, offering a systematic way of understanding trending patient confidence in their drug brands.
Tracking this Patient Confidence Score enables pharma to accurately measure the effectiveness of marketing campaigns, reduce budgets, improve market competitiveness and deliver better health outcomes for patients.
Talking Medicines was formed in 2013 by a group of experienced entrepreneurs with sector expertise in life sciences, marketing and data tech. Led by CEO Jo Halliday alongside co-founders Dr Elizabeth Fairley and Dr Scott Crae the company, based in Glasgow UK, has raised $3.4m (£2.5m) funding to date, including a $1.5m (£1.1m) funding deal with Tern Plc in November last year.
Jo Halliday, CEO of Talking Medicines said: “The pharmaceutical sector spends $30Bn on marketing each year in the US alone* without really knowing if that investment is doing any good. The systematic data driven tools that other industries use to measure customer experience haven’t been available to pharma at scale and the industry has relied on indirect feedback from clinicians, patient advocacy or ad hoc focus groups.
“What we’re able to do with PatientMetRx is de-risk social data collection for pharma by offering arm’s length and agile data collection from wherever the patient is speaking and decoding it to align to medicines. We’re able to do something that has never been done before and make sense of the patient voice once a drug has been launched to generate pharma grade intelligence.
“By using cutting edge artificial intelligence, machine learning and natural language processing models, we’re able provide real time social intelligence in a straightforward and incredibly intuitive way.
“It’s been a glaring omission that medication research hasn’t been able to tap in to the voice of the patient like this but the feedback we’ve had from the industry so far has shown how vital an insight tool like PatientMetRx is.
“Marketing spend can be more efficient, patient outcome will be better.”
Subscription to PatientMtRx provides access to data on a chosen medicine brand and a competitor brand, highlighting trends within the dynamic Patient Confidence Score as well as diagnostics on what the score means. Users can also view volume for patient voice by selected medicine, customise dates and produce PDF reports. A Pro subscription adds the ability to select up to 10 brands to view trending patient confidence over time.
Attached free-use image shows Jo Halliday, (CEO of Talking Medicines). Higher resolution images are available from https://we.tl/t-BcjuuLLZFl
Notes to editors:
About Talking Medicines
Talking Medicines is the world’s first social intelligence company designed specifically for the pharmaceutical industry. By structuring and translating the patient’s voice on social media into actionable intelligence, it helps pharma deliver a greater return on investment for marketing, and better health outcomes for patients.
Where do you get your data from?
PatientMetRx uses text mining technologies, collected from a multitude of online channels from high volume sites such as Reddit and Twitter to more specific patient centric data sources such as forums or connected devices. This data is coupled with Talking Medicines’ own AI, machine learning and natural language processing technologies which filters text at scale, to isolate the voice of the patient, and match that to regulated, approved medicines.
What drugs does the system benchmark?
Talking Medicines’ proprietary knowledge database of curated medicines is at the core of EVA, its AI machine. The Talking Medicine database covers clinical and packaging data on 130k UK and US medicines, which it actively keeps up to date through liaison with global regulatory bodies.
What is the quality of PatientMetRx data?
Quality is paramount throughout the data collection process all the way through to the presentation of insights. Talking Medicines applies statistical quality control methods to ensure that high standards are robustly met for its pharmaceutical industry clients.