Savana and The COPD Foundation Partner to Accelerate Innovative Clinical Research into COPD

July 12, 2021

New partnership set to accelerate innovative AI-powered deep Real World Evidence research into finding the missing millions with Chronic Obstructive Pulmonary Disease (COPD) and address unmet needs.

NY, New York, 12 July 2021. - Savana, world leader in deep Real World Evidence (deep RWE) clinical research, and US not-for-profit organization The COPD Foundation announced today that they are partnering to accelerate innovative clinical research into COPD.

The partnership will unlock the clinical data from de-identified, free text in Electronic Health Records (EHRs) to establish a predictive model to identify patients who may have COPD but have not yet been diagnosed. The research aims to find individuals with "pre-COPD" based on known risk factors, and identify commonly used medications that may be associated with improved outcomes for individuals with COPD or those at risk for developing COPD.

The US COPD challenge

Over 16 million people in the United States have COPD1, and up to 60% of COPD cases go undiagnosed.2 According to the World Health Organization, COPD is the third leading cause of death globally and a significant driver of global healthcare costs.3 COPD and symptomatic pre-COPD continue to be a leading cause of disabling symptoms and suffering.

The COPD Foundation was established to improve the lives of people with COPD, bronchiectasis, and nontuberculous mycobacterial (NTM) lung disease through initiatives that expand services and speed innovations which will make treatment more effective and affordable. The COPD Foundation does this through scientific research, education, advocacy and awareness with the goal of disease prevention, slowed progression, and ultimately a cure.

Identifying an unmet need in COPD

"Our new partnership with Savana will complement and extend The COPD Foundation’s ongoing program of research – specifically in the drive to find young individuals with disease and understand how they are diagnosed and treated. Through our Digital Health and Therapeutics Accelerator Network, COPD360Net, we are poised to conduct innovative clinical trials where we can utilize the predictive model developed from this relationship to make a difference for our community," said Ruth Tal-Singer, PhD, President and Chief Science Officer, The COPD Foundation.

Dr. Ignacio Medrano, Chief Medical Officer, and Founder, Savana said: "We are absolutely delighted to be supporting the work of The COPD Foundation and contributing deep Real World Evidence research to their ambitious package of ongoing research activity into alleviating the burden of COPD on patients, caregivers and health services. A partnership such as this, with a US-based, not-for-profit health organization, is the first of its kind for Savana. It marks another milestone in our growing international ecosystem of researchers, research institutions and sponsors seeking to use innovative deep RWE studies to identify unmet need, gain new insights and answer novel questions in respiratory health and many other specialties.""

Unlocking real-world evidence health data

Savana will apply its deep RWE – an AI-driven clinical research methodology to unlock the health data trapped within EHRs.

Research has found that up to 80% of useful clinical information, including signs, symptoms, and diagnosis of disease, is contained within the free-text ‘unstructured’ portion of the EHR and written in natural language.

Savana has developed ©EHRead4, a powerful technology that applies Artificial Intelligence (AI) in the form of Natural Language Processing (NLP) and deep learning techniques to analyze both structured and unstructured information in EHRs, while safeguarding the privacy and security of patient data.

Safeguarding patient data is key

Ensuring the transparent and responsible use of patients’ data and patient data privacy and security is at the core of Savana’s working practices.

Patient EHR data will remain entirely under the control of the participating research sites. Savana technology and research methodology support layers of patient data privacy and security, including anonymization of patient records, aggregation of study data, and the use of Savana’s patented data privacy methodology - Natural Privacy5.

Founded in 2014, Savana is an international medical company that has developed a scientific methodology that applies Artificial Intelligence (AI) to unlock all the clinical value embedded within the free text of Electronic Health Records (EHRs). With the largest AI-enabled, multi-language, multi-centre research network in the world, Savana generates customised descriptive and predictive, Deep Real World Evidence research studies. Engineered by doctors for doctors, Savana is built following the highest privacy-by-design standards. Savana constitutes a clinical research ecosystem that aims to advance personalied and precision medicine worldwide. Please visit or follow us on LinkedIn and Twitter.

The partnership with the COPD Foundation is complementary to Savana’s ongoing respiratory health initiative comprising deep RWE studies and a growing international research ecosystem by developing ways to identify individuals with COPD, pre-COPD, bronchiectasis, and NTM lung disease or people at risk for developing the condition to inform the development of new treatments.

About the COPD Foundation
The COPD Foundation is a not-for-profit organization that was established to improve the lives of people with COPD, bronchiectasis, and NTM lung disease through initiatives that expand services and speed innovations which will make treatment more effective and affordable. We do this through scientific research, education, advocacy, and awareness with the goal of disease prevention, slowed progression, and ultimately a cure. The COPD Foundation leadership and Medical and Scientific advisory committee includes representatives of the lung community, clinical science, genetics, and the social sciences (bioethics, economics, and/or law). Please visit our website or follow us on LinkedIn and Twitter.

About COPD360Net
COPD360Net’s mission is to support the development and adoption of novel digital health tools, medical devices and therapeutics that treat COPD, bronchiectasis, and nontuberculous mycobacterial (NTM) lung disease. This network consists of the core COPD Foundation accredited care centers; experts in COPD and related lung diseases; relevant subject matter experts, including primary care physicians; clinical trial designers; health economists and psychosocial experts, all working together to devise creative ways to support patients and their families in every aspect of their lives. COPD360Net is governed by a steering committee that includes clinical lead experts from participating centers, key content specialists and both patient and caregiver representatives.

Savana media inquiries:
Sarah Fisher
Marketing Lead
+44 (0) 7711 773855

The COPD Foundation media inquiries:
Carol Johnson
Director of Communications


  1. COPD. Centers for Disease Control and Prevention. Published June 6, 2018. Accessed December 28, 2020.
  2. Martinez C, Mannino DM, Jaimes FA, et al. Undiagnosed obstructive lung disease in the U.S. Ann ATS. 2015;(12):1788-1795.
  3. World Health Organization. The top 10 causes of death. Published December 9, 2020. Accessed February 7, 2021.
  4. About ©EHRead: ©EHRead automatically processes anonymised, de-identified, unlinked patient text documents from EHRs within the participating research institution and returns aggregated, data-rich medical information to the researchers five times faster than traditional RWE research methods. Researchers are able view and analyse this information through the user-friendly interface of Savana Manager and use the results to support clinical research and practice.
  5. About Natural Privacy: This methodology ensures that all identifiable personal information and patient record identifiers have been completely stripped from the record before use, and that the resulting data is converted into a synthetic clinical database that is demonstrably clinically accurate in aggregated format.