Does In Vitro Potency Predict Clinically Efficacious Concentrations?

Discovery of a CK2α'-Biased ATP-Competitive Inhibitor from a High-Throughput Screen of an Allosteric-Inhibitor-Like Compound Library

Protein kinase CK2 is a holoenzyme composed of two regulatory subunits (CK2β) and two catalytic subunits (CK2α and CK2α'). CK2 controls several cellular processes, including proliferation, inflammation, and cell death. However, CK2α and CK2α' possess different expression patterns and substrates and therefore impact each of these processes differently. Elevated CK2α participates in the development of cancer, while increased CK2α' has been associated with neurodegeneration, especially Huntington's disease (HD). HD is a fatal disease for which no effective therapies are available. Genetic deletion of CK2α' in HD mouse models has ameliorated neurodegeneration. Therefore, pharmacological inhibition of CK2α' presents a promising therapeutic strategy for treating HD. However, current CK2 inhibitors are unable to discriminate between CK2α and CK2α' due to their high structural homology, especially in the targeted ATP-binding site. Using computational analyses, we found a potential type IV ("D" pocket) allosteric site that contained different residues between CK2α and CK2α' and was distal from the ATP-binding pocket featured in both kinases. We decided to look for allosteric modulators that might interact in a biased fashion with the type IV pocket on both CK2α and CK2α'. We screened a commercial library containing ∼29,000 allosteric-kinase-inhibitor-like compounds using a CK2α' activity-dependent ADP-Glo Kinase assay. Obtained hits were counter-screened against CK2α using the ADP-Glo Kinase assay, revealing two CK2α'-biased compounds. These two compounds might serve as the basis for further medicinal chemistry optimization for the potential treatment of HD.

Targeting mTOR and survivin concurrently potentiates radiation therapy in renal cell carcinoma by suppressing DNA damage repair and amplifying mitotic catastrophe

BACKGROUND

Renal cell carcinoma (RCC) was historically considered to be less responsive to radiation therapy (RT) compared to other cancer indications. However, advancements in precision high-dose radiation delivery through single-fraction and multi-fraction stereotactic ablative radiotherapy (SABR) have led to better outcomes and reduced treatment-related toxicities, sparking renewed interest in using RT to treat RCC. Moreover, numerous studies have revealed that certain therapeutic agents including chemotherapies can increase the sensitivity of tumors to RT, leading to a growing interest in combining these treatments. Here, we developed a rational combination of two radiosensitizers in a tumor-targeted liposomal formulation for augmenting RT in RCC. The objective of this study is to assess the efficacy of a tumor-targeted liposomal formulation combining the mTOR inhibitor everolimus (E) with the survivin inhibitor YM155 (Y) in enhancing the sensitivity of RCC tumors to radiation.

EXPERIMENTAL DESIGN

We slightly modified our previously published tumor-targeted liposomal formulation to develop a rational combination of E and Y in a single liposomal formulation (EY-L) and assessed its efficacy in RCC cell lines in vitro and in RCC tumors in vivo. We further investigated how well EY-L sensitizes RCC cell lines and tumors toward radiation and explored the underlying mechanism of radiosensitization.

RESULTS

EY-L outperformed the corresponding single drug-loaded formulations E-L and Y-L in terms of containing primary tumor growth and improving survival in an immunocompetent syngeneic mouse model of RCC. EY-L also exhibited significantly higher sensitization of RCC cells towards radiation in vitro than E-L and Y-L. Additionally, EY-L sensitized RCC tumors towards radiation therapy in xenograft and murine RCC models. EY-L mediated induction of mitotic catastrophe via downregulation of multiple cell cycle checkpoints and DNA damage repair pathways could be responsible for the augmentation of radiation therapy.

CONCLUSION

Taken together, our study demonstrated the efficacy of a strategic combination therapy in sensitizing RCC to radiation therapy via inhibition of DNA damage repair and a substantial increase in mitotic catastrophe. This combination therapy may find its use in the augmentation of radiation therapy during the treatment of RCC patients.

Metabolite Bioanalysis in Drug Development: Recommendations from the IQ Consortium Metabolite Bioanalysis Working Group

The intent of this perspective is to share the recommendations of the International Consortium for Innovation and Quality in Pharmaceutical Development Metabolite Bioanalysis Working Group on the fit-for-purpose metabolite bioanalysis in support of drug development and registration. This report summarizes the considerations for the trigger, timing, and rigor of bioanalysis in the various assessments to address unique challenges due to metabolites, with respect to efficacy and safety, which may arise during drug development from investigational new drug (IND) enabling studies, and phase I, phase II, and phase III clinical trials to regulatory submission. The recommended approaches ensure that important drug metabolites are identified in a timely manner and properly characterized for efficient drug development.

Explaining in-vitro to in-vivo efficacy correlations in oncology pre-clinical development via a semi-mechanistic mathematical model

In-vitro to in-vivo correlations (IVIVC), relating in-vitro parameters like IC50 to in-vivo drug exposure in plasma and tumour growth, are widely used in oncology for experimental design and dose decisions. However, they lack a deeper understanding of the underlying mechanisms. Our paper therefore focuses on linking empirical IVIVC relations for small-molecule kinase inhibitors with a semi-mechanistic tumour-growth model. We develop an approach incorporating parameters like the compound's peak-trough ratio (PTR), Hill coefficient of in-vitro dose-response curves, and xenograft-specific properties. This leads to formulas for determining efficacious doses for tumor stasis under linear pharmacokinetics equivalent to traditional empirical IVIVC relations, but enabling more systematic analysis. Our findings reveal that in-vivo xenograft-specific parameters, specifically the growth rate (g) and decay rate (d), along with the average exposure, are generally more significant determinants of tumor stasis and effective dose than the compound's peak-trough ratio. However, as the Hill coefficient increases, the dependency of tumor stasis on the PTR becomes more pronounced, indicating that the compound is more influenced by its maximum or trough values rather than the average exposure. Furthermore, we discuss the translation of our method to predict population dose ranges in clinical studies and propose a resistance mechanism that solely relies on specific in-vivo xenograft parameters instead of IC50 exposure coverage. In summary, our study aims to provide a more mechanistic understanding of IVIVC relations, emphasizing the importance of xenograft-specific parameters and PTR on tumor stasis.

Repurposing calcium-sensing receptor activator drug cinacalcet for ADPKD treatment

ADPKD is characterized by progressive cyst formation and enlargement leading to kidney failure. Tolvaptan is currently the only FDA-approved treatment for ADPKD; however, it can cause serious adverse effects including hepatotoxicity. There remains an unmet clinical need for effective and safe treatments for ADPKD. The extracellular Ca2+-sensing receptor (CaSR) is a regulator of epithelial ion transport. FDA-approved CaSR activator cinacalcet can reduce cAMP-induced Cl- and fluid secretion in various epithelial cells by activating phosphodiesterases (PDE) that hydrolyze cAMP. Since elevated cAMP is a key mechanism of ADPKD progression by promoting cell proliferation, cyst formation and enlargement (via Cl- and fluid secretion), here we tested efficacy of cinacalcet in cell and animal models of ADPKD. Cinacalcet treatment reduced cAMP-induced Cl- secretion and CFTR activity in MDCK cells as suggested by ∼70 % lower short-circuit current (Isc) changes in response to forskolin and CFTRinh-172, respectively. Cinacalcet treatment inhibited forskolin-induced cAMP elevation by 60 % in MDCK cells, and its effect was completely reversed by IBMX (PDE inhibitor). In MDCK cells treated with forskolin, cinacalcet treatment concentration-dependently reduced cell proliferation, cyst formation and cyst enlargement by up to 50 % without affecting cell viability. Cinacalcet treatment (20 mg/kg/day for 7 days, subcutaneous) reduced renal cyst index in a mouse model of ADPKD (Pkd1flox/flox;Ksp-Cre) by 20 %. Lastly, cinacalcet treatment reduced cyst enlargement and cell proliferation in human ADPKD cells by 60 %. Considering its efficacy as shown here, and favorable safety profile including extensive post-approval data, cinacalcet can be repurposed as a novel ADPKD treatment.

Human Dose and Pharmacokinetic Predictions for Biologics at Boehringer Ingelheim: A Retrospective Analysis

INTRODUCTION

Accurate predictions of pharmacokinetics and efficacious doses for biologics in humans are critical for selecting appropriate first-in-human starting doses and dose ranges and for estimating clinical material needs and cost of goods. This also impacts clinical feasibility, particularly for subcutaneously administered biologics.

METHODS

We performed a comprehensive comparison between predicted and observed clearances and doses in humans for a set of 22 biologic drugs developed at Boehringer Ingelheim (BI) over the last 2 decades. The analysis included biologics across three therapeutic areas comprising a wide variety of modalities: mono- and bispecific monoclonal antibodies (mAbs) and nanobodies and a Fab fragment.

RESULTS

Our analysis showed that observed clearances in humans were within twofold of predicted clearances for 17 out of 20 biologics (85%). Six biologics had uncharacteristically high observed human clearances (range 32-280 mL/h) for their respective molecular classes, impacting their clinical developability. For three molecules, molecular characteristics contributed to the high clearance. Clinically selected doses were within twofold of predicted for 58% of projects. With 42% and 25% of projects selecting clinical doses higher than two- or threefold the predicted value, respectively, the importance of better understanding not only the pharmacokinetic (PK) but also the predictivity of pharmacodynamic models is highlighted.

CONCLUSIONS

We provide a clinical pharmacology perspective on the commonly accepted twofold range of human clearance predictions as well as the implications of higher than predicted targeted efficacious plasma concentration on clinical development. Finally, an analysis of key success factors for biologics at BI was conducted, which may be relevant for the entire pharmaceutical industry. This is one of the largest retrospective analyses for biologics and provides further evidence that successful predictions of human PK and efficacious dose will be further facilitated by gathering key translational data early in research.

Translatability of in vitro potency to clinical efficacious exposure: A retrospective analysis of FDA-approved targeted small molecule oncology drugs

In vitro potency is one of the important parameters representing efficacy potential of drugs and commonly used as benchmark of efficacious exposure at early clinical development. There are limited numbers of studies which systematically investigate on how predictive in vitro potency is to estimate therapeutic drug exposure, especially those focusing on targeted anticancer agents despite the recent increase in approvals. This study aims to fill in such knowledge gaps. A total of 87 small molecule targeted drugs approved for oncology indication between 2001 and 2020 by the US Food and Drug Administration (FDA) were identified; relevant preclinical and clinical data were extracted from the public domain. Relationships between the in vitro potency and the therapeutic dose or exposure (unbound average drug concentration [Cu,av ] as the primary exposure metrics) were assessed by descriptive analyses. The Spearman's rank correlation test showed slightly better correlation of the Cu,av (ρ = 0.232, p = 0.041) rather than the daily dose (ρ = 0.186, p = 0.096) with the in vitro potency. Better correlation was observed for the drugs for hematologic malignancies compared with those for solid tumors (root mean square error: 140 [n = 28] versus 297 [n = 59]). The present study shows that in vitro potency is predictive to estimate the therapeutic drug exposure to some extent, whereas the general trend of overexposure was observed. The results suggested that in vitro potency alone is not sufficient and robust enough to estimate the clinically efficacious exposure of molecularly targeted small molecule oncology drugs. The totality of data, including both nonclinical and clinical, needs to be considered for dose optimization.

Markedly divergent effects of Ouabain on a Temozolomide-resistant (T98G) vs. a Temozolomide-sensitive (LN229) Glioblastoma cell line

BACKGROUND

Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor with poor prognosis. GMB are highly recurrent mainly because of radio- and chemoresistance. Radiotherapy with Temozolomide (TMZ) is until today the golden standard adjuvant therapy, however, the optimal treatment of recurrent glioblastoma remains controversial. Ouabain belongs to the Cardiotonic Steroids (CTS) the natural ligands of the Na/K-ATPase (NKA). It is established that the NKA represents a signal transducer with either stimulating or inhibiting cell growth, apoptosis, migration and angiogenesis. Over the last decade evidence grew that CTS have anti-tumor properties especially in GBM.

AIM

Proceeding from recent studies we wanted to further demonstrate a divergent effect of Ouabain on a TMZ-resistant (T98G) as compared to a TMZ-sensitive (LN229) GBM cell line.

METHODS

We analyzed the effect of Ouabain on cell migration and plasma cell membrane potential (PCMP) in the LN229 and T98G GBM cell line as well as underlying mechanisms (Bcl-2 and p-Akt/pan-Akt expression). Moreover, we analyzed the anti-angiogenic effect of Ouabain on human umbilical vein endothelial cells (HUVECs).

RESULTS

T98G cells showed a significant inhibition of cell migration and a significant depolarization of the PCMP at similar Ouabain concentrations (IC50 = 1.67 × 10^-7 M) resp. (IC50 = 2.72 × 10^-7 M) with a strong inverse correlation (R² = 0.95). In contrast, LN229 cells did not respond to Ouabain in these assays at all. Similarly, only T98G but not LN229 cells revealed Bcl-2 down-regulation at nanomolar Ouabain concentrations. This unique response to Ouabain is associated with a down-regulation of pan-Akt in T98G cells 24 h after Ouabain (1.0 × 10^-6 M) treatment. For the first time, the anti-angiogenic effect of Ouabain on HUVEC cells (IC50 = 5.49 × 10^-8 M) was demonstrated which correlated strongly with the anti-migratory effect (R² = 0.85).

CONCLUSION

The TMZ-resistant T98G cell line as compared to the TMZ-sensitive LN229 cell line shows a high sensitivity towards Ouabain. We consider it as a promising new compound especially in recurrent GBM to overcome the resistance to TMZ and irradiation.

Novel Efficient Multistage Lead Optimization Pipeline Experimentally Validated for DYRK1B Selective Inhibitors

In addition to general challenges in drug discovery such as the identification of lead compounds in time- and cost-effective ways, specific challenges also exist. Particularly, it is necessary to develop pharmacological inhibitors that effectively discriminate between closely related molecular targets. DYRK1B kinase is considered a valuable target for cancer-specific mono- or combination chemotherapy; however, the inhibition of its closely related DYRK1A kinase is not beneficial. Existing inhibitors target both kinases with essentially the same efficiency, and the unavailability of the DYRK1B crystal structure makes the discovery of DYRK1B-specific inhibitors even more challenging. Here, we propose a novel multi-stage compound discovery pipeline aimed at in silico identification of both potent and selective small molecules from a large set of initial candidates. The method uses structure-based docking and ligand-based quantitative structure–activity relationship modeling. This approach allowed us to identify lead and runner-up small-molecule compounds targeting DYRK1B with high efficiency and specificity.

Exploiting pretrained biochemical language models for targeted drug design

MOTIVATION

The development of novel compounds targeting proteins of interest is one of the most important tasks in the pharmaceutical industry. Deep generative models have been applied to targeted molecular design and have shown promising results. Recently, target-specific molecule generation has been viewed as a translation between the protein language and the chemical language. However, such a model is limited by the availability of interacting protein-ligand pairs. On the other hand, large amounts of unlabelled protein sequences and chemical compounds are available and have been used to train language models that learn useful representations. In this study, we propose exploiting pretrained biochemical language models to initialize (i.e. warm start) targeted molecule generation models. We investigate two warm start strategies: (i) a one-stage strategy where the initialized model is trained on targeted molecule generation and (ii) a two-stage strategy containing a pre-finetuning on molecular generation followed by target-specific training. We also compare two decoding strategies to generate compounds: beam search and sampling.

RESULTS

The results show that the warm-started models perform better than a baseline model trained from scratch. The two proposed warm-start strategies achieve similar results to each other with respect to widely used metrics from benchmarks. However, docking evaluation of the generated compounds for a number of novel proteins suggests that the one-stage strategy generalizes better than the two-stage strategy. Additionally, we observe that beam search outperforms sampling in both docking evaluation and benchmark metrics for assessing compound quality.

AVAILABILITY AND IMPLEMENTATION

The source code is available at https://github.com/boun-tabi/biochemical-lms-for-drug-design and the materials (i.e., data, models, and outputs) are archived in Zenodo at https://doi.org/10.5281/zenodo.6832145.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Translational Pharmacokinetic–Pharmacodynamic Modeling of NaV1.7 Inhibitor MK-2075 to Inform Human Efficacious Dose

MK-2075 is a small-molecule selective inhibitor of the NaV1.7 channel investigated for the treatment of postoperative pain. A translational strategy was developed for MK-2075 to quantitatively interrelate drug exposure, target modulation, and the desired pharmacological response in preclinical animal models for the purpose of human translation. Analgesics used as a standard of care in postoperative pain were evaluated in preclinical animal models of nociceptive behavior (mouse tail flick latency and rhesus thermode heat withdrawal) to determine the magnitude of pharmacodynamic (PD) response at plasma concentrations associated with efficacy in the clinic. MK-2075 was evaluated in those same animal models to determine the concentration of MK-2075 required to achieve the desired level of response. Translation of MK-2075 efficacious concentrations in preclinical animal models to a clinical PKPD target in humans was achieved by accounting for species differences in plasma protein binding and in vitro potency against the NaV1.7 channel. Estimates of human pharmacokinetic (PK) parameters were obtained from allometric scaling of a PK model from preclinical species and used to predict the dose required to achieve the clinical exposure. MK-2075 exposure–response in a preclinical target modulation assay (rhesus olfaction) was characterized using a computational PKPD model which included a biophase compartment to account for the observed hysteresis. Translation of this model to humans was accomplished by correcting for species differences in PK NaV1.7 potency, and plasma protein binding while assuming that the kinetics of distribution to the target site is the same between humans and rhesus monkeys. This enabled prediction of the level of target modulation anticipated to be achieved over the dosing interval at the projected clinical efficacious human dose. Integration of these efforts into the early development plan informed clinical study design and decision criteria.

For whom the T cells troll? Bispecific T-cell engagers in glioblastoma

Glioblastoma is the the most common primary brain tumor in adults. Onset of disease is followed by a uniformly lethal prognosis and dismal overall survival. While immunotherapies have revolutionized treatment in other difficult-to-treat cancers, these have failed to demonstrate significant clinical benefit in patients with glioblastoma. Obstacles to success include the heterogeneous tumor microenvironment (TME), the immune-privileged intracranial space, the blood-brain barrier (BBB) and local and systemic immunosuppressions. Monoclonal antibody-based therapies have failed at least in part due to their inability to access the intracranial compartment. Bispecific T-cell engagers are promising antibody fragment-based therapies which can bring T cells close to their target and capture them with a high binding affinity. They can redirect the entire repertoire of T cells against tumor, independent of T-cell receptor specificity. However, the multiple challenges posed by the TME, immune privilege and the BBB suggest that a single agent approach may be insufficient to yield durable, long-lasting antitumor efficacy. In this review, we discuss the mechanism of action of T-cell engagers, their preclinical and clinical developments to date. We also draw comparisons with other classes of multispecific antibodies and potential combinations using these antibody fragment therapies.

Enantiospecific antitrypanosomal in vitro activity of eflornithine

The polyamine synthesis inhibitor eflornithine is a recommended treatment for the neglected tropical disease Gambian human African trypanosomiasis in late stage. This parasitic disease, transmitted by the tsetse fly, is lethal unless treated. Eflornithine is administered by repeated intravenous infusions as a racemic mixture of L-eflornithine and D-eflornithine. The study compared the in vitro antitrypanosomal activity of the two enantiomers with the racemic mixture against three Trypanosoma brucei gambiense strains. Antitrypanosomal in vitro activity at varying drug concentrations was analysed by non-linear mixed effects modelling. For all three strains, L-eflornithine was more potent than D-eflornithine. Estimated 50% inhibitory concentrations of the three strains combined were 9.1 μM (95% confidence interval [8.1; 10]), 5.5 μM [4.5; 6.6], and 50 μM [42; 57] for racemic eflornithine, L-eflornithine and D-eflornithine, respectively. The higher in vitro potency of L-eflornithine warrants further studies to assess its potential for improving the treatment of late-stage Gambian human African trypanosomiasis.

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

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.

Development of a Physiologically Based Pharmacokinetic Model for Hydroxychloroquine and Its Application in Dose Optimization in Specific COVID-19 Patients

In Feb 2020, we developed a physiologically-based pharmacokinetic (PBPK) model of hydroxychloroquine (HCQ) and integrated in vitro anti-viral effect to support dosing design of HCQ in the treatment of COVID-19 patients in China. This, along with emerging research and clinical findings, supported broader uptake of HCQ as a potential treatment for COVID-19 globally at the beginning of the pandemics. Therefore, many COVID-19 patients have been or will be exposed to HCQ, including specific populations with underlying intrinsic and/or extrinsic characteristics that may affect the disposition and drug actions of HCQ. It is critical to update our PBPK model of HCQ with adequate drug absorption and disposition mechanisms to support optimal dosing of HCQ in these specific populations. We conducted relevant in vitro and in vivo experiments to support HCQ PBPK model update. Different aspects of this model are validated using PK study from 11 published references. With parameterization informed by results from monkeys, a permeability-limited lung model is employed to describe HCQ distribution in the lung tissues. The updated model is applied to optimize HCQ dosing regimens for specific populations, including those taking concomitant medications. In order to meet predefined HCQ exposure target, HCQ dose may need to be reduced in young children, elderly subjects with organ impairment and/or coadministration with a strong CYP2C8/CYP2D6/CYP3A4 inhibitor, and be increased in pregnant women. The updated HCQ PBPK model informed by new metabolism and distribution data can be used to effectively support dosing recommendations for clinical trials in specific COVID-19 patients and treatment of patients with malaria or autoimmune diseases.

Time-Dependent Distribution of Hydroxychloroquine in Cynomolgus Macaques Using Population Pharmacokinetic Modeling Method

To evaluate the biodistribution of hydroxychloroquine (HCQ) in cynomolgus macaques and receive dynamic quantitative relationship between plasma, blood, and lung tissue concentration using the population pharmacokinetic modeling method, seventeen cynomolgus macaques were divided into six groups according to different HCQ dosing regimens over 5 days. The monkeys were euthanized, and blood, plasma, urine, feces and ten tissues were collected. All the samples were prepared by protein precipitation and analyzed by HPLC-MS/MS detection. The population pharmacokinetics of HCQ in the plasma, red blood cells, and lung tissue was conducted and simulated via ADAPT program. Results demonstrated that the maximum concentration (C max) of HCQ was 292.33 ng/mL in blood and 36.90 ng/mL in plasma after single dose of 3 mg/kg. The value of area under curve (AUC0-∞) was determined as 5,978.94 and 363.31 h* ng/mL for the blood and plasma, respectively. The descending order of the tissue-to-plasma concentration ratio was liver > spleen > kidney > lung > heart > subcutaneous fat > brain. The tissue-to-plasma concentration ratio and the tissue-to-blood concentration ratio for lung were found to be time-dependent with 267.38 and 5.55 at 120 h postdose, respectively. A five-compartment model with first-order oral absorption and elimination best described the plasma, blood, and lung tissue pharmacokinetics. The estimated elimination rate constant (ke) for a typical monkey was 0.236 h-1. The volume of distribution in central (Vc/F) and other two peripheral compartments (Vb/F and Vl/F) were 114, 2.68, and 5.55 L, respectively. Model-based simulation with PK parameters from cynomolgus macaques showed that the ratio of the blood or plasma to lung tissue was a dynamic change course, which suggested that the rate of HCQ concentration decrease in the blood or plasma was faster than that in the lung tissue. HCQ was found to be accumulated in tissues, especially in the liver, kidney, lung, and spleen. Also, the tissue-to-plasma concentration ratio increased over time. The population pharmacokinetic model developed could allow for the assessment of pharmacokinetics-pharmacodynamics relationships, especially relevant tissue concentration-response for HCQ. Determining appropriate treatment regimens in animals allows translation of these to clinical studies.

Application of the Nested Enzyme-Within-Enterocyte (NEWE) Turnover Model for Predicting the Time Course of Pharmacodynamic Effects

The gut wall consists of many biological elements, including enterocytes. Rapid turnover, a prominent feature of the enterocytes, has generally been ignored in the development of enterocyte-targeting drugs, although it has a comparable rate to other kinetic rates. Here, we investigated the impact of enterocyte turnover on the pharmacodynamics of enterocyte-targeting drugs by applying a model accounting for turnover of enterocytes and target proteins. Simulations showed that the pharmacodynamics depend on enterocyte lifespan when drug-target affinity is strong and half-life of target protein is long. Interindividual variability of enterocyte lifespan, which can be amplified by disease conditions, has a substantial impact on the variability of response. However, our comprehensive literature search showed that the enterocyte turnover causes a marginal impact on currently approved enterocyte-targeting drugs due to their relatively weak target affinities. This study proposes a model-informed drug development approach for selecting enterocyte-targeting drugs and their optimal dosage regimens.