Lenacapavir Sodium

Long acting (LA) drug products extend the effect of a single dose for weeks or months, offering new options for disease prevention and treatment. However, regulatory guidance on LA drug product development and equivalence remains limited. The existing Biopharmaceutics Classification System (BCS) guides the development and approval of small-molecule oral drug substances. There is no such classification system for LA drug products. Most LA drug products are given as subcutaneous (SC) or intramuscular (IM) injectables. We propose a new Classification System for Biopharmaceutics of Long-Acting Parenteral Products, designated as CS-BLAP. This classification system focuses on products instead of drug substances. CS-BLAP covers LA products beyond those based on conventional depot/sustained drug-release strategies and includes small- and macro-molecules (biologics) designed with or without delivery system and engineered to transit through lymph instead of directly penetrating the blood. We found that the molecular or particle size of drugs assembled as LA products is the basis of the classification in determining the route/mechanism of parenteral drug absorption. Depending on the product size, SC or IM injectables may preferentially penetrate blood or lymphatic capillaries. Based on their selectivity in lymph vs blood uptake, retention, and transit, LA products are classified as: Class I: Small molecules, absorption mainly via blood after release from depot products; Class II: Small molecules, absorption of drug-in-carrier via lymph;Class III: Biologics, absorption mainly via blood after release from depot products; Class IV: Biologics, absorption via lymph. The CS-BLAP proposal is supported by a dataset of drugs and endogenous molecules spanning a range of molecular weights and particle sizes. From these datasets, a predictive model estimated the lymph-to-blood absorption fraction as a function of apparent molecular size. The mid-transition point occurs around 35 kDa, where the drug substance (either free or associated with a delivery system) distributes equally between lymph and blood (50:50). Increasing molecular size progressively favor distribution through the lymphatic pathway, estimated to be 70 % at 50 kDa, 80 % at 66 kDa, and >90 % beyond 90 kDa. The time-to-peak plasma concentration (T_max) serves as a surrogate marker to qualify non-depot drug products absorption, with longer T_max values indicating delayed lymphatic drug transit. Case studies are presented, including how GLP-1 derivatives are designed to produce LA drug products and their proposed classification assignments under CS-BLAP. In addition, an injectable solution of lenacapavir that form solid at injection site may be viewed as a sustained release or depot product, but it could be regulated as an injectable pharmaceutical solution for product bioequivalency. The proposed CS-BLAP framework could serve as a foundation for scientists in design and development, for regulators in evaluation and approval, and for sponsors in planning post-approval scaling of long-acting products.

HIV evades immune detection through rapid mutation of its surface proteins, yet essential steps in viral entry, such as CD4 and co-receptor engagement, remain highly conserved. While therapies like Lenacapavir represent major advances, the emergence of resistant strains highlights the urgent need for adaptable, rapid-response antivirals. This challenge extends beyond HIV, demanding scalable design strategies for diverse viral threats. Here, we demonstrate that AI-driven design can address this need by generating cyclic peptide binders targeting a previously unexploited interface on the HIV-1 fusion protein gp41. Using only sequence information, without prior structural or binding site data, we designed and experimentally validated a single candidate. This inhibitor potently blocked infection by two HIV-1 strains in cell-based assays with no detectable cytotoxicity. Affinity analysis with SPR confirms the interaction with gp41 as designed. Our findings illustrate how AI-guided peptide design, coupled with rapid in-vitro validation, can accelerate early-stage therapeutic discovery and enable timely intervention against emerging viral threats.