Guiding dose selection of monoclonal antibodies using a new parameter (AFTIR) for characterizing ligand binding systems

Ahmed, Sameed; Ellis, Miandra; Li, Hongshan; Pallucchini, Luca; Stein, Andrew M.

doi:10.1007/s10928-019-09638-3

Cited by 12 publications

(17 citation statements)

References 28 publications

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“…45, which we call the "simple" ASIR formula, large drug concentrations were required; for arbitrarily small doses and drug concentrations, ASIR simple approaches infinity. This property was also observed in the derivation for AFTIR [4]. An expression for ASIR that holds over small drug concentrations should approach one for small doses since T L ss should approach T L 0 .…”

Section: Approximating Asir At Low Drug Concentrationssupporting

confidence: 54%

“…AFIR is the Average Free target to Initial target Ratio for target inhibition in circulation [3], and AFTIR is the Average Free Tissue target to Initial target Ratio in the tissue of interest (e.g. a tumor) [4]. The formulas for both metrics are provided below:…”

Section: A U T H O R Accepted Manuscript 24 Definition Of Previous Inhibition Metrics: Afir and Aftirmentioning

confidence: 99%

“…A summary of IC 50 expressions for four different ligand binding systems is shown in Figure 3. The results are based on the work from this paper as well as on previous studies that explored different compartmental models [3,4,18]. Throughout the rest of this manuscript, the term SSIM will refer to the inhibition metric for the competitive TMDD model shown in Figure 2; we will derive this expression and the IC 50 value for this system.…”

Section: Definition Of Asir and Ssimmentioning

confidence: 99%

“…Recently, two metrics [3,4] have been developed for predicting target engagement in circulation and in the target tissue. However, these (and most other) target engagement metrics do not account for the binding of the target to its endogenous ligand.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.

Alaybeyoglu

Cheng

Doshi

et al. 2021

J Pharmacokinet Pharmacodyn

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Keywords monoclonal antibody • target mediated drug disposition • pharmacokinetics and pharmacodynamics • pharmacometrics Abstract Predictions for target engagement are often used to guide drug development. In particular, when selecting the recommended phase 2 dose of a drug that is very safe, and where good biomarkers for response may not exist (e.g. in immuno-oncology), a receptor occupancy prediction could even be the main determinant in justifying the approved dose, as was the case for atezolizumab. The underlying assumption in these models is that when the drug binds its target, it disrupts the interaction between the target and its endogenous ligand, thereby disrupting downstream signaling. However, the interaction between the target and its endogenous binding partner is almost never included in the model. In this work, we take a deeper look at the in vivo system where a drug binds to its target and disrupts the target's interaction with an endogenous ligand. We derive two simple steady state inhibition metrics (SSIMs) for the system, which provides intuition for when the competition between drug and endogenous ligand should be taken into account for guiding drug development.

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Section: Approximating Asir At Low Drug Concentrationssupporting

confidence: 54%

Section: A U T H O R Accepted Manuscript 24 Definition Of Previous Inhibition Metrics: Afir and Aftirmentioning

confidence: 99%

Section: Definition Of Asir and Ssimmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.

Alaybeyoglu

Cheng

Doshi

et al. 2021

J Pharmacokinet Pharmacodyn

Self Cite

View full text Add to dashboard Cite

show abstract

“…TMDD models have been widely applied in model-informed drug development of therapeutic antibodies. Antibody-target binding kinetics can be considered in the PK/PD models to predict the desirable antibody properties [205,206]. Antibodies with a high target affinity are desirable in the early stage of development for achieving a high and durable target coverage [207].…”

Section: Optimizing Target Binding Affinitymentioning

confidence: 99%

Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions

Tang

Cao

2021

Pharmaceutics

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With more than 90 approved drugs by 2020, therapeutic antibodies have played a central role in shifting the treatment landscape of many diseases, including autoimmune disorders and cancers. While showing many therapeutic advantages such as long half-life and highly selective actions, therapeutic antibodies still face many outstanding issues associated with their pharmacokinetics (PK) and pharmacodynamics (PD), including high variabilities, low tissue distributions, poorly-defined PK/PD characteristics for novel antibody formats, and high rates of treatment resistance. We have witnessed many successful cases applying PK/PD modeling to answer critical questions in therapeutic antibodies’ development and regulations. These models have yielded substantial insights into antibody PK/PD properties. This review summarized the progress, challenges, and future directions in modeling antibody PK/PD and highlighted the potential of applying mechanistic models addressing the development questions.

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Sabatolimab (MBG453) model‐informed drug development for dose selection in patients with myelodysplastic syndrome/acute myeloid leukemia and solid tumors

Zhang

Rinne

et al. 2023

CPT Pharmacom & Syst Pharma

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Sabatolimab is a novel immunotherapy with immuno‐myeloid activity that targets T‐cell immunoglobulin domain and mucin domain‐3 (TIM‐3) on immune cells and leukemic blasts. It is being evaluated for the treatment of myeloid malignancies in the STIMULUS clinical trial program. The objective of this analysis was to support the sabatolimab dose‐regimen selection in hematologic malignancies. A population pharmacokinetic (PopPK) model was fit to patients with solid tumors and hematologic malignancies, which included acute myeloid leukemia, myelodysplastic syndrome (including intermediate‐, high‐, and very high‐risk per Revised International Prognostic Scoring System), and chronic myelomonocytic leukemia. The PopPK model, together with a predictive model of sabatolimab distribution to the bone marrow and binding to TIM‐3 was used to predict membrane‐bound TIM‐3 bone marrow occupancy. In addition, the total soluble TIM‐3 (sTIM‐3) kinetics and the pharmacokinetic (PK) exposure‐response relationship in patients with hematologic malignancies were examined. At intravenous doses above 240 mg Q2w and 800 mg Q4w, we observed linear PK, a plateau in the accumulation of total sTIM‐3, and a flat exposure‐response relationship for both safety and efficacy. In addition, the model predicted membrane‐bound TIM‐3 occupancy in the bone marrow was above 95% in over 95% of patients. Therefore, these results support the selection of the 400 mg Q2w and 800 mg Q4w dosing regimens for the STIMULUS clinical trial program.

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Guiding dose selection of monoclonal antibodies using a new parameter (AFTIR) for characterizing ligand binding systems

Cited by 12 publications

References 28 publications

Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.

Estimating drug potency in the competitive target mediated drug disposition (TMDD) system when the endogenous ligand is included.

Modeling Pharmacokinetics and Pharmacodynamics of Therapeutic Antibodies: Progress, Challenges, and Future Directions

Sabatolimab (MBG453) model‐informed drug development for dose selection in patients with myelodysplastic syndrome/acute myeloid leukemia and solid tumors

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