Amivantamab by Johnson & Johnson for Colorectal Cancer: Likelihood of Approval

GlobalData tracks drug-specific phase transition and likelihood of approval scores, in addition to indication benchmarks based off 18 years of historical drug development data. Attributes of the drug, company and its clinical trials play a fundamental role in drug-specific PTSR and likelihood of approval.

Amivantamab overview

Amivantamab-vmjw (Rybrevant) is a low-fucose human immunoglobulin G1-based bispecific antibody developed using recombinant DNA technology. It is formulated as solution and concentrate for solution for intravenous infusion. Amivantamab is indicated for the treatment of  adult patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) exon 20 insertion mutations, as detected by an FDA-approved test, whose disease has progressed on or after platinum-based chemotherapy.

Amivantamab is under development for the treatment of non-small-cell lung cancer (NSCLC), squamous cell carcinoma of the head and neck (SCCHN), hepatocellular cancer (HCC), colorectal cancer (CRC), metastatic colorectal cancer, esophageal cancer, renal cell cancer (RCC), medullary thyroid cancer (MTC), gastroesophageal cancer (GEC), mesothelioma, breast cancer (BC) and ovarian cancer (OC). It is administered as an intravenous and subcutaneous infusion. The drug candidate is a bi-specific monoclonal antibody that targets EGFr and cMet with exon-20 insertion. It is based on DuoBody technology platform. The drug candidate is a new molecular entity (NME).

For a complete picture of Amivantamab’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 16 August 2023

GlobalData

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Likelihood of Approval analytics tool dynamically assesses and predicts how likely a drug will move to the next stage in clinical development (PTSR), as well as how likely the drug will be approved (LoA). This is based on a combination of machine learning and a proprietary algorithm to process data points from various databases found on GlobalData’s Pharmaceutical Intelligence Center.