Abstract

Abstract Our nanoparticle-drug conjugates (NDCs), created at Cerulean Pharma Inc. by conjugating drug payloads to our novel β-cyclodextrin-PEG (CDP) copolymer, are designed to significantly mitigate a payload’s limitations by providing sustained drug delivery to the tumor and superior therapeutic index through controlled release kinetics. Cerulean has two NDCs in the clinic, CRLX101 and CRLX301, evidencing the translatability of our technology. CRLX101 has been dosed in over 400 patients and CRLX301 is in ongoing Phase 2a development. A key and differentiating feature of our NDC Platform is our linker technology, which is tailored for an optimal fit with the conjugation functionality of the API drug payloads (e.g., alcohol, carboxylic acid, amine, amide and urea functionality) and customizable to achieve desired drug release profiles. As an illustration of Cerulean’s ability to expand its NDC platform, we will present the biological and pharmacokinetic (PK) data supporting our drug combination platform of antibody nanoparticle-drug conjugates (ANDCs) and multi-drug nanoparticle-drug conjugates (mNDCs). ANDCs combine potentially any NDC with any conjugatable biologic to generate an ANDC with ultra-high drug-antibody ratios (DARs). Using our established NDC linker technology, we generated Herceptin-camptothecin ANDCs with DARs as high as 500, orders of magnitude higher than ADCs, and no more than 5-fold loss in binding (greater than 90% binding up to 300 DAR) compared to native Herceptin in our solution-based HER2 antigen binding assay. In addition, we provide evidence experimentally that rhodamine-labeled ANDCs penetrate and internalize in HER2+ tumor cells. The ANDCs demonstrate tunable in vitro release kinetics and long in vivo half lives in mouse PK studies, including sustained levels of released drug in tumors (greater than 300h) using an ANDC (average DAR 201) delivering an 8 mg/kg camptothecin dose. The observed mouse MTD for the ANDC was at least 3x higher than that of the corresponding NDC. The mNDCs take advantage of our existing NDC linker platform technology to conjugate diverse drug combos including DNA damaging agents (DDA) + DNA damage repair agents (DDR). We generated our POC camptothecin-olaparib mNDCs spanning a range of drug combination ratios (from 1:1 to 1:20) and all demonstrated distinguishable and tunable in vitro release rates. PK study of a 1:1 camptothecin-olaparib mNDC (~8mg/kg each drug) demonstrated very low clearance and sustained levels of released drug in tumor (greater than 72h). Our drug combination platforms, ANDCs and mNDCs, allow delivery of therapeutic agents to their respective biological targets at clinically-relevant doses, greatly increasing the diversity of drug combination possibilities. Note: This abstract was not presented at the meeting. Citation Format: Chester A. Metcalf, Derek van der Poll, Liang Zhao, Roy I. Case, Doug Lazarus, Donna Brown, Tiffany Halo, Lata Jayaraman, Christian Peters, Ellen Rohde, Scott Eliasof. Sustained and controlled in vivo therapeutic levels of drug payloads in tumors using two separate drug combination platforms: Antibody nanoparticle-drug conjugates and multi-drug nanoparticle-drug conjugates, with the potential for improved drug combinability and anticancer effects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5135. doi:10.1158/1538-7445.AM2017-5135

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.