September 12, 2019. If the United States is to regain the stature of offering a top-notch healthcare system that is the model for other countries and make the most of our considerable investment in personalized and precision medicine, PCORI must be sustained.
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NCHR Comment on FDA’s Draft Guidance Regarding Use of an Alternate Name for Potassium Chloride in Food Labeling
September 17, 2019. NCHR supports the name “potassium salt” in the ingredient statement as an alternative to the name “potassium chloride.” The name “potassium salt” would be more understandable to consumers and manufacturers, thereby facilitating sodium reductions in processed foods and improving public health.
Read More »NCHR Comments on FDA’s Draft Guidance on Enhancing the Diversity of Clinical Trial Populations
August 6, 2019. There are reasons why a drug or device may be less safe or less effective for women, children, older patients, or certain ethnic or racial subgroups. These differences in results for under-represented subgroups may not be minor or trivial. This is why sufficient inclusion of under-represented groups is so important.
Read More »NCHR Comments on FDA’s Guidance on Post-Approval Pregnancy Safety Studies
June 28, 2019: NCHR public comment urges FDA to require safety studies of drugs taken during or after pregnancy that include women of all races, ethnicities and access to insurance. FDA should require better tracking of medication risks, and ensuring that research represents all races, ethnicities, and insurance types (including uninsured women and those on Medicaid). With 9 out of 10 pregnant women taking medications, we need better safety data to protect both mothers and babies.
Read More »NCHR Comment on Regulating Artificial Intelligence/Machine Learning-Based Software
June 3, 2019. Artificial Intelligence/Machine Learning (AI/ML)-based software device that incorporates special computer techniques (algorithms) capable of detecting relevant medical patterns from large amounts of data. These very sophisticated pattern recognition capabilities (AI/ML) have broad potential healthcare applications, including making recommendations to healthcare providers and patients about the diagnosis, prognosis, treatment, or prevention of disease.1 The complexity, scalability, and broad scope of these new technologies thus raise important issues regarding their safety and effectiveness as it pertains to patients’ health.
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