Merck has been granted a patent for cyclic polypeptide compounds that can bind to human PCSK9, potentially reducing LDL cholesterol levels. The compounds may inhibit interaction between PCSK9 and LDLR. This innovation could lead to new pharmaceutical compositions for lowering cholesterol levels. GlobalData’s report on Merck gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Merck, Human telomerase RT biomarker was a key innovation area identified from patents. Merck's grant share as of May 2024 was 53%. Grant share is based on the ratio of number of grants to total number of patents.
A recently granted patent (Publication Number: US12012468B2) discloses a cyclic peptide formula aimed at reducing low-density lipoprotein (LDL) cholesterol levels in individuals with hypercholesterolemia. The patent claims include the cyclic peptide formula, pharmaceutical compositions containing the peptide, and methods for administering the peptide to treat hypercholesterolemia and inhibit PCSK9 activity. The cyclic peptide is designed to inhibit the interaction between human PCSK9 and the epidermal growth factor-like repeat A (EGF-A) domain of human LDLR, ultimately reducing LDL cholesterol levels in patients.
The patent also covers methods for treating hypercholesterolemia in individuals with comorbidities such as nephrotic syndrome, kidney failure, coronary artery disease, atherosclerosis, stroke, peripheral vascular disease, diabetes, and high blood pressure. The administration of the cyclic peptide can be done through various routes such as oral, intravenous, intramuscular, intraperitoneal, subcutaneous, transdermal, and intravitreal. By targeting PCSK9 activity and the interaction between PCSK9 and LDLR, the patented cyclic peptide offers a promising approach to managing hypercholesterolemia and related conditions, providing a potential therapeutic option for individuals in need of cholesterol-lowering treatments.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies
