In relapsed or refractory diffuse large B-cell lymphoma, CD19 expression by immunohistochemistry alone is not a predictor of response to loncastuximab tesirine

CD19-targeting treatments have shown promise in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL). Loncastuximab tesirine (loncastuximab tesirine-lpyl [Lonca]) is a CD19-targeting antibody-drug conjugate indicated for R/R DLBCL after at least two systemic treatments. CD19 expression was evaluated in patients receiving Lonca in the LOTIS-2 clinical trial with available tissue samples obtained after last systemic therapy/before Lonca treatment. Lonca cytotoxicity was evaluated in a panel of six lymphoma cell lines with various CD19 expression levels. Quantitative systems pharmacology (QSP) modelling was used to predict Lonca responses. Lonca responses were seen in patients across all CD19 expression levels, including patients with low/no detectable CD19 expression and H-scores at baseline. Similarly, Lonca induced cytotoxicity in cell lines with different levels of CD19 expression, including one with very low expression. QSP modelling predicted that CD19 expression by immunohistochemistry alone does not predict Lonca response, whereas inclusion of CD19 surface density improved response prediction. Virtual patients responded to Lonca with estimated CD19 as low as 1000 molecules/cell of CD19, normally below the immunohistochemistry detection level. We found Lonca is an effective treatment for R/R DLBCL regardless of CD19 expression by immunohistochemistry. These results provide the basis for future studies addressing CD19-targeted agent sequencing.

A Quantitative Modeling and Simulation Framework to Support Candidate and Dose Selection of Anti-SARS-CoV-2 Monoclonal antibodies to Advance Bamlanivimab into a First-in-Human Clinical Trial

Neutralizing monoclonal antibodies (mAb), novel therapeutics for the treatment of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2), have been urgently researched from the start of the pandemic. The selection of the optimal mAb candidate and therapeutic dose were expedited using open‐access in silico models. The maximally effective therapeutic mAb dose was determined through two approaches; both expanded on innovative, open‐science initiatives. A physiologically‐based pharmacokinetic (PBPK) model, incorporating physicochemical properties predictive of mAb clearance and tissue distribution, was used to estimate mAb exposure that maintained concentrations above 90% inhibitory concentration of in vitro neutralization in lung tissue for up to 4 weeks in 90% of patients. To achieve fastest viral clearance following onset of symptoms, a longitudinal SARS‐CoV‐2 viral dynamic model was applied to estimate viral clearance as a function of drug concentration and dose. The PBPK model‐based approach suggested that a clinical dose between 175 and 500 mg of bamlanivimab would maintain target mAb concentrations in the lung tissue over 28 days in 90% of patients. The viral dynamic model suggested a 700 mg dose would achieve maximum viral elimination. Taken together, the first‐in‐human trial (NCT04411628) conservatively proceeded with a starting therapeutic dose of 700 mg and escalated to higher doses to evaluate the upper limit of safety and tolerability. Availability of open‐access codes and application of novel in silico model‐based approaches supported the selection of bamlanivimab and identified the lowest dose evaluated in this study that was expected to result in the maximum therapeutic effect before the first‐in‐human clinical trial.