Improving Anti-CD45 Antibody Radioimmunotherapy Using a Physiologically Based Pharmacokinetic Model

SAAM II: A general mathematical modeling rapid prototyping environment

Simulation Analysis and Modeling II (SAAM II) is a graphical modeling software used in life sciences for compartmental model analysis, particularly, but not exclusively, appreciated in pharmacokinetics (PK) and pharmacodynamics (PD), metabolism, and tracer modeling. Its intuitive "circles and arrows" visuals allow users to easily build, solve, and fit compartmental models without the need for coding. It is suitable for rapid prototyping of models for complex kinetic analysis or PK/PD problems, and in educating students and non-modelers. Although it is straightforward in design, SAAM II incorporates sophisticated algorithms programmed in C to address ordinary differential equations, deal with complex systems via forcing functions, conduct multivariable regression featuring the Bayesian maximum a posteriori, perform identifiability and sensitivity analyses, and offer reporting functionalities, all within a single package. After 26 years from the last SAAM II tutorial paper, we demonstrate here SAAM II's updated applicability to current life sciences challenges. We review its features and present four contemporary case studies, including examples in target-mediated PK/PD, CAR-T-cell therapy, viral dynamics, and transmission models in epidemiology. Through such examples, we demonstrate that SAAM II provides a suitable interface for rapid model selection and prototyping. By enabling the fast creation of detailed mathematical models, SAAM II addresses a unique requirement within the mathematical modeling community.

Physiologically based radiopharmacokinetic (PBRPK) modeling to simulate and analyze radiopharmaceutical therapies: studies of non-linearities, multi-bolus injections, and albumin binding

BACKGROUND

We aimed to develop a publicly shared computational physiologically based pharmacokinetic (PBPK) model to reliably simulate and analyze radiopharmaceutical therapies (RPTs), including probing of hot-cold ligand competitions as well as alternative injection scenarios and drug designs, towards optimal therapies.

RESULTS

To handle the complexity of PBPK models (over 150 differential equations), a scalable modeling notation called the "reaction graph" is introduced, enabling easy inclusion of various interactions. We refer to this as physiologically based radiopharmacokinetic (PBRPK) modeling, fine-tuned specifically for radiopharmaceuticals. As three important applications, we used our PBRPK model to (1) study the effect of competition between hot and cold species on delivered doses to tumors and organs at risk. In addition, (2) we evaluated an alternative paradigm of utilizing multi-bolus injections in RPTs instead of prevalent single injections. Finally, (3) we used PBRPK modeling to study the impact of varying albumin-binding affinities by ligands, and the implications for RPTs. We found that competition between labeled and unlabeled ligands can lead to non-linear relations between injected activity and the delivered dose to a particular organ, in the sense that doubling the injected activity does not necessarily result in a doubled dose delivered to a particular organ (a false intuition from external beam radiotherapy). In addition, we observed that fractionating injections can lead to a higher payload of dose delivery to organs, though not a differential dose delivery to the tumor. By contrast, we found out that increased albumin-binding affinities of the injected ligands can lead to such a differential effect in delivering more doses to tumors, and this can be attributed to several factors that PBRPK modeling allows us to probe.

CONCLUSIONS

Advanced computational PBRPK modeling enables simulation and analysis of a variety of intervention and drug design scenarios, towards more optimal delivery of RPTs.

Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model

INTRODUCTION

Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-based pharmacokinetic (PBPK) model, a nonlinear mixed effect (NLME) model, and single-time-point imaging to calculate the TIACs and ADs of ⁹⁰Y-DOTATATE in various organs of dosimetric interest and tumors.

MATERIALS & METHODS

Biokinetic data of ¹¹¹In-DOTATATE in tumors, kidneys, liver, spleen, and whole body were obtained from eight patients using planar scintigraphic imaging at T1 = (2.9 ± 0.6), T2 = (4.6 ± 0.4), T3 = (22.8 ± 1.6), T4 = (46.7 ± 1.7) and T5 = (70.9 ± 1.0) h post injection. Serum activity concentration was measured at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d p.i.. A published PBPK model for PRRT, NLME, and a single-time-point imaging datum at different time points were used to calculate TIACs in tumors, kidneys, liver, spleen, whole body, and serum. Relative deviations (RDs) (median [min, max]) between the calculated TIACs from single-time-point imaging were compared to the TIACs calculated from the all-time-points fit. The root mean square error (RMSE) of the difference between the computed ADs from the single-time-point imaging and reference ADs from the all-time point fittings were analyzed. A joint root mean square error RMSE_joint of the ADs was calculated with the RSME from both the tumor and kidneys to sort the time points concerning accurate results for the kidneys and tumor dosimetry. The calculations of TIACs and ADs from the single-time-point dosimetry were repeated using the sum of exponentials (SOE) approach introduced in the literature. The RDs and the RSME of the PBPK approach in our study were compared to the SOE approach.

RESULTS

Using the PBPK and NLME models and the biokinetic measurements resulted in a good fit based on visual inspection of the fitted curves and the coefficient of variation CV of the fitted parameters (<50%). T4 was identified being the time point with a relatively low median and range of TIACs RDs, i.e., 5 [1, 21]% and 2 [-15, 21]% for kidneys and tumors, respectively. T4 was found to be the time point with the lowest joint root mean square error RMSE_joint of the ADs. Based on the RD and RMSE, our results show a similar performance as the SOE and NLME model approach.

SUMMARY

In this study, we introduced a simplified calculation of TIACs/ADs using a PBPK model, an NLME model, and a single-time-point measurement. Our results suggest a single measurement might be used to calculate TIACs/ADs in the kidneys and tumors during PRRT.

Evaluation of [225Ac]Ac-DOTA-anti-VLA-4 for targeted alpha therapy of metastatic melanoma

Very late antigen 4 (VLA-4; also called integrin α4β1) is overexpressed in melanoma tumor cells with an active role in tumor growth, angiogenesis, and metastasis, making VLA-4 a potential target for targeted alpha therapy (TAT).

METHODS

An anti-VLA-4 antibody was conjugated to DOTA for [²²⁵Ac]Ac-labeling and DTPA for [¹¹¹In]In-labeling. The resulting agents, [²²⁵Ac]Ac- or [¹¹¹In]In-labeled anti-VLA-4 were evaluated in vitro, including binding affinity, internalization, and colony formation assays as well as in vivo biodistribution studies. In addition, the therapeutic efficacy of [²²⁵Ac]Ac-DOTA-anti-VLA-4 was evaluated in a disseminated disease mouse model of melanoma.

RESULTS

[¹¹¹In]In-DTPA-anti-VLA-4 demonstrated high affinity for VLA-4 (K_d = 5.2 ± 1.6 nM). [²²⁵Ac]Ac-DOTA-anti-VLA-4 was labeled with an apparent molar activity of 3.5 MBq/nmol and > 95% radiochemical purity. Colony formation assays demonstrated a decrease in the surviving fraction of B16F10 cells treated with [²²⁵Ac]Ac-DOTA-anti-VLA-4 compared to control. Biodistribution studies demonstrated accumulation in the VLA-4-positive tumor and VLA-4 rich organs. Therapeutic efficacy studies demonstrated a significant increase in survival in mice treated with [²²⁵Ac]Ac-DOTA-anti-VLA-4 as compared to controls.

CONCLUSION

The work presented here demonstrated that [²²⁵Ac]Ac-DOTA-anti-VLA-4 was effective as a treatment in mice with disseminated disease, but potentially has dose limiting hematopoietic toxicity. Preliminary studies presented here also supported the potential to overcome this limitation by exploring a pre-loading or blocking dose strategy, to optimize the targeting vector to help minimize the absorbed dose to VLA-4 rich organs while maximizing the dose delivered to VLA-4-positive melanoma tumor cells.

A new pharmacokinetic model for 90Y-ibritumomab tiuxetan based on 3-dimensional dosimetry

Monoclonal antibodies (mAbs) are key components in several therapies for cancer and inflammatory diseases but current knowledge of their clinical pharmacokinetics and distribution in human tissues remains incomplete. Consequently, optimal dosing and scheduling in clinics are affected. With sequential radiolabeled mAb-based imaging, radiation dosing in tissues/organs can be calculated to provide a better assessment of mAb concentrations in tissues. This is the first pharmacokinetic model of ⁹⁰Y-Ibritumomab tiuxetan (⁹⁰Y-IT) in humans to be described, based on three-dimensional (3D) dosimetry using single-photon emission computed-tomography coupled with computed-tomography. 19 patients with follicular lymphoma were treated initially with ⁹⁰Y-IT in the FIZZ trial. Based on a compartmental approach individualising the vascular compartment within studied organs, this study proposes a reliable pharmacokinetic (PK) five-compartment model replacing the currently used two-compartment model and constitutes a new direction for further research. This model provides exchange constants between the different tissues, Area Under the Curve of ¹¹¹In-IT in blood (AUC) and Mean Residence Time (MRT) that have not been reported so far for IT. Finally, the elimination process appears to occur in a compartment other than the liver or the spleen and suggests the metabolism of mAbs may take place mainly on the vascular compartment level.

The Effect of Total Tumor Volume on the Biologically Effective Dose to Tumor and Kidneys for 177Lu-Labeled PSMA Peptides

The aim of this work was to simulate the effect of prostate-specific membrane antigen (PSMA)-positive total tumor volume (TTV) on the biologically effective doses (BEDs) to tumors and organs at risk in patients with metastatic castration-resistant prostate cancer who are undergoing ¹⁷⁷Lu-PSMA radioligand therapy. Methods: A physiologically based pharmacokinetic model was fitted to the data of 13 patients treated with ¹⁷⁷Lu-PSMA I&T (a PSMA inhibitor for imaging and therapy). The tumor, kidney, and salivary gland BEDs were simulated for TTVs of 0.1-10 L. The activity and peptide amounts leading to an optimal tumor-to-kidneys BED ratio were also investigated. Results: When the TTV was increased from 0.3 to 3 L, the simulated BEDs to tumors, kidneys, parotid glands, and submandibular glands decreased from 22 ± 15 to 11.0 ± 6.0 Gy_1.49, 6.5 ± 2.3 to 3.7 ± 1.4 Gy_2.5, 11.0 ± 2.7 to 6.4 ± 1.9 Gy_4.5, and 10.9 ± 2.7 to 6.3 ± 1.9 Gy_4.5, respectively (where the subscripts denote that an α/β of 1.49, 2.5, or 4.5 Gy was used to calculate the BED). The BED to the red marrow increased from 0.17 ± 0.05 to 0.32 ± 0.11 Gy₁₅ For patients with a TTV of more than 0.3 L, the optimal amount of peptide was 273 ± 136 nmol and the optimal activity was 10.4 ± 4.4 GBq. Conclusion: This simulation study suggests that in patients with large PSMA-positive tumor volumes, higher activities and peptide amounts can be safely administered to maximize tumor BEDs without exceeding the tolerable BED to the organs at risk.

Treatment planning in PRRT based on simulated PET data and a PBPK model

Aim: To investigate the accuracy of treatment planning in peptide-receptor radionuclide therapy (PRRT) based on simulated PET data (using a PET noise model) and a physiologically based pharmacokinetic (PBPK) model. Methods: The parameters of a PBPK model were fitted to the biokinetic data of 15 patients. True mathematical phantoms of patients (MPPs) were the PBPK model with the fitted parameters. PET measurements after bolus injection of 150 MBq 68Ga-DOTATATE were simulated for the true MPPs. PET noise with typical noise levels was added to the data (i.e. c=0.3 [low], 3, 30 and 300 [high]). Organ activity data in the kidneys, tumour, liver and spleen were simulated at 0.5, 1 and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 3.3 GBq of 90Y-DOTATATE over 30 min. Time-integrated activity coefficients (TIACs) of simulated therapy in tumour, kidneys, liver, spleen and remainder were calculated from both, true MPPs (true TIACs) and predicted MPPs (predicted TIACs). Variability v between true TIACs and predicted TIACs were calculated and analysed. Variability< 10 % was considered to be an accurate prediction. Results: For all noise level, variabilities for the kidneys, liver, and spleen showed an accurate prediction for TIACs, e.g. c=300: vkidney=(5 ± 2)%, vliver=(5 ± 2)%, vspleen=(4 ± 2)%. However, tumour TIAC predictions were not accurate for all noise levels, e.g. c=0.3: vtumour=(8 ± 5)%. Conclusion: PET based treatment planning with kidneys as the dose limiting organ seems possible for all reported noise levels using an adequate PBPK model and previous knowledge about the individual patient.

Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model: A simulation study on the effect of sampling schedule and noise

PURPOSE

The aim of this study was to investigate the accuracy of PET-based treatment planning for predicting the time-integrated activity coefficients (TIACs).

METHODS

The parameters of a physiologically based pharmacokinetic (PBPK) model were fitted to the biokinetic data of 15 patients to derive assumed true parameters and were used to construct true mathematical patient phantoms (MPPs). Biokinetics of 150 MBq (68)Ga-DOTATATE-PET was simulated with different noise levels [fractional standard deviation (FSD) 10%, 1%, 0.1%, and 0.01%], and seven combinations of measurements at 30 min, 1 h, and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data using population-based Bayesian parameters to construct predicted MPPs. Therapy simulations were performed as 30 min infusion of (90)Y-DOTATATE of 3.3 GBq in both true and predicted MPPs. Prediction accuracy was then calculated as relative variability vorgan between TIACs from both MPPs.

RESULTS

Large variability values of one time-point protocols [e.g., FSD = 1%, 240 min p.i., vkidneys = (9 ± 6)%, and vtumor = (27 ± 26)%] show inaccurate prediction. Accurate TIAC prediction of the kidneys was obtained for the case of two measurements (1 and 4 h p.i.), e.g., FSD = 1%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 10)%, or three measurements, e.g., FSD = 1%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 9)%.

CONCLUSIONS

(68)Ga-DOTATATE-PET measurements could possibly be used to predict the TIACs of (90)Y-DOTATATE when using a PBPK model and population-based Bayesian parameters. The two time-point measurement at 1 and 4 h p.i. with a noise up to FSD = 1% allows an accurate prediction of the TIACs in kidneys.

Physiologically based pharmacokinetic models of small molecules and therapeutic antibodies: a mini-review on fundamental concepts and applications

The mechanisms of absorption, distribution, metabolism and elimination of small and large molecule therapeutics differ significantly from one another and can be explored within the framework of a physiologically based pharmacokinetic (PBPK) model. This paper briefly reviews fundamental approaches to PBPK modeling, in which drug kinetics within tissues and organs are explicitly represented using physiologically meaningful parameters. The differences in PBPK models applied to small/large molecule drugs are highlighted, thus elucidating differences in absorption, distribution and elimination properties between these two classes of drugs in a systematic manner. The absorption of small and large molecules differs with respect to their common extravascular routes of delivery (oral versus subcutaneous). The role of the lymphatic system in drug distribution, and the involvement of tissues as sites of elimination (through catabolism and target mediated drug disposition) are unique features of antibody distribution and elimination that differ from small molecules, which are commonly distributed into the tissues but are eliminated primarily by liver metabolism. Fundamental differences exist in the ability to predict human pharmacokinetics based upon preclinical data due to differing mechanisms governing small and large molecule disposition. These differences have influence on the evolving utilization of PBPK modeling in the discovery and development of small and large molecule therapeutics.

Optimized Peptide Amount and Activity for ⁹⁰Y-Labeled DOTATATE Therapy

In peptide receptor radionuclide therapy with (90)Y-labeled DOTATATE, the kidney absorbed dose limits the maximum amount of total activity that can be safely administered in many patients. A higher tumor-to-kidney absorbed dose ratio might be achieved by optimizing the amount of injected peptide and activity, as recent studies have shown different degrees of receptor saturation for normal tissue and tumor. The aim of this work was to develop and implement a modeling method for treatment planning to determine the optimal combination of peptide amount and pertaining therapeutic activity for each patient.

METHODS

A whole-body physiologically based pharmacokinetic (PBPK) model was developed. General physiologic parameters were taken from the literature. Individual model parameters were fitted to a series (n= 12) of planar γ-camera and serum measurements ((111)In-DOTATATE) of patients with meningioma or neuroendocrine tumors (NETs). Using the PBPK model and the individually estimated parameters, we determined the tumor, liver, spleen, and red marrow biologically effective doses (BEDs) for a maximal kidney BED (20 Gy2.5) for different peptide amounts and activities. The optimal combination of peptide amount and activity for maximal tumor BED, considering the additional constraint of a red marrow BED less than 1 Gy15, was individually quantified.

RESULTS

The PBPK model describes the biokinetic data well considering the criteria of visual inspection, the coefficients of determination, the relative standard errors (<50%), and the correlation of the parameters (<0.8). All fitted parameters were in a physiologically reasonable range but varied considerably between patients, especially tumor perfusion (meningioma, 0.1-1 mL·g(-1)·min(-1), and NETs, 0.02-1 mL·g(-1)·min(-1)) and receptor density (meningioma, 5-34 nmol·L(-1), and NETs, 7-35 nmol·L(-1)). Using the proposed method, we identified the optimal amount and pertaining activity to be 76 ± 46 nmol (118 ± 71 μg) and 4.2 ± 1.8 GBq for meningioma and 87 ± 50 nmol (135 ± 78 μg) and 5.1 ± 2.8 GBq for NET patients.

CONCLUSION

The presented work suggests that to achieve higher efficacy and safety for (90)Y-DOATATE therapy, both the administered amount of peptide and the activity should be optimized in treatment planning using the proposed method. This approach could also be adapted for therapy with other peptides.

The role of patient-based treatment planning in peptide receptor radionuclide therapy

BACKGROUND

Accurate treatment planning is recommended in peptide-receptor radionuclide therapy (PRRT) to minimize the toxicity to organs at risk while maximizing tumor cell sterilization. The aim of this study was to quantify the effect of different degrees of individualization on the prediction accuracy of individual therapeutic biodistributions in patients with neuroendocrine tumors (NETs).

METHODS

A recently developed physiologically based pharmacokinetic (PBPK) model was fitted to the biokinetic data of 15 patients with NETs after pre-therapeutic injection of (111)In-DTPAOC. Mathematical phantom patients (MPP) were defined using the assumed true (true MPP), mean (MPP 1A) and median (MPP 1B) parameter values of the patient group. Alterations of the degree of individualization were introduced to both mean and median patients by including patient-specific information as a priori knowledge: physical parameters and hematocrit (MPP 2A/2B). Successively, measurable individual biokinetic parameters were added: tumor volume V tu (MPP 3A/3B), glomerular filtration rate GFR (MPP 4A/4B), and tumor perfusion f tu (MPP 5A/5B). Furthermore, parameters of MPP 5A/5B and a simulated (68)Ga-DOTATATE PET measurement 60 min p.i. were used together with the population values used as Bayesian parameters (MPP 6A/6B). Therapeutic biodistributions were simulated assuming an infusion of (90)Y-DOTATATE (3.3 GBq) over 30 min to all MPPs. Time-integrated activity coefficients were predicted for all MPPs and compared to the true MPPs for each patient in tumor, kidneys, spleen, liver, remainder, and whole body to obtain the relative differences RD.

RESULTS

The large RD values of MPP 1A [RDtumor = (625 ± 1266)%, RDkidneys = (11 ± 38)%], and MPP 1B [RDtumor = (197 ± 505)%, RDkidneys = (11 ± 39)%] demonstrate that individual treatment planning is needed due to large physiological differences between patients. Although addition of individual patient parameters reduced the deviations considerably [MPP 5A: RDtumor = (-2 ± 27)% and RDkidneys = (16 ± 43)%; MPP 5B: RDtumor = (2 ± 28)% and RDkidneys = (7 ± 40)%] errors were still large. For the kidneys, prediction accuracy was considerably improved by including the PET measurement [MPP 6A/MPP 6B: RDtumor = (-2 ± 22)% and RDkidneys = (-0.1 ± 0.5)%].

CONCLUSION

Individualized treatment planning is needed in the investigated patient group. The use of a PBPK model and the inclusion of patient specific data, e.g., weight, tumor volume, and glomerular filtration rate, do not suffice to predict the therapeutic biodistribution. Integrating all available a priori information in the PBPK model and using additionally PET data measured at one time point for tumor, kidneys, spleen, and liver could possibly be sufficient to perform an individualized treatment planning.

The NUKDOS software for treatment planning in molecular radiotherapy

The aim of this work was the development of a software tool for treatment planning prior to molecular radiotherapy, which comprises all functionality to objectively determine the activity to administer and the pertaining absorbed doses (including the corresponding error) based on a series of gamma camera images and one SPECT/CT or probe data. NUKDOS was developed in MATLAB. The workflow is based on the MIRD formalism For determination of the tissue or organ pharmacokinetics, gamma camera images as well as probe, urine, serum and blood activity data can be processed. To estimate the time-integrated activity coefficients (TIAC), sums of exponentials are fitted to the time activity data and integrated analytically. To obtain the TIAC on the voxel level, the voxel activity distribution from the quantitative 3D SPECT/CT (or PET/CT) is used for scaling and weighting the TIAC derived from the 2D organ data. The voxel S-values are automatically calculated based on the voxel-size of the image and the therapeutic nuclide ((90)Y, (131)I or (177)Lu). The absorbed dose coefficients are computed by convolution of the voxel TIAC and the voxel S-values. The activity to administer and the pertaining absorbed doses are determined by entering the absorbed dose for the organ at risk. The overall error of the calculated absorbed doses is determined by Gaussian error propagation. NUKDOS was tested for the operation systems Windows(®) 7 (64 Bit) and 8 (64 Bit). The results of each working step were compared to commercially available (SAAMII, OLINDA/EXM) and in-house (UlmDOS) software. The application of the software is demonstrated using examples form peptide receptor radionuclide therapy (PRRT) and from radioiodine therapy of benign thyroid diseases. For the example from PRRT, the calculated activity to administer differed by 4% comparing NUKDOS and the final result using UlmDos, SAAMII and OLINDA/EXM sequentially. The absorbed dose for the spleen and tumour differed by 7% and 8%, respectively. The results from the example from radioiodine therapy of benign thyroid diseases and the example given in the latest corresponding SOP were identical. The implemented, objective methods facilitate accurate and reproducible results. The software is freely available.

Treatment planning in molecular radiotherapy

In molecular radiotherapy a radionuclide or a radioactively labelled pharmaceutical is administered to the patient. Treatment planning therefore comprises the determination of activity to administer. This administered activity should maximize tumour cell sterilization while minimizing normal tissue damage. In this work we present different approaches that are frequently used for determining the suitable activity. These approaches may be cohort- based as in chemotherapy, or patient-specific using dosimetry based on individual biokinetics. The approaches are different with respect to the input complexity, the corresponding costs and - in consequence - the quality of the therapy. In addition, a general scheme for data collection and analysis is proposed. To develop an effective and safe treatment, elaborate data need to be obtained. The main challenges, however, are collecting these complex data and analyse them properly.

Issues, challenges, and opportunities in model-based drug development for monoclonal antibodies

Over the last two decades, there has been a simultaneous explosion in the levels of activity and capability in both monoclonal antibody (mAb) drug development and in the use of quantitative pharmacologic models to facilitate drug development. Both of these topics are currently areas of great interest to academia, the pharmaceutical and biotechnology industries, and to regulatory authorities. In this article, we summarize convergence of these two areas and discuss some of the current and historical applications of the use of mathematical-model-based techniques to facilitate the discovery and development of mAb therapeutics. We also consider some of the current issues and limitations in model-based antibody discovery/development and highlight areas of further opportunity.

Differences in predicted and actually absorbed doses in peptide receptor radionuclide therapy

PURPOSE

An important assumption in dosimetry prior to radionuclide therapy is the equivalence of pretherapeutic and therapeutic biodistribution. In this study the authors investigate if this assumption is justified in sst2-receptor targeting peptide therapy, as unequal amounts of peptide and different peptides for pretherapeutic measurements and therapy are commonly used.

METHODS

Physiologically based pharmacokinetic models were developed. Gamma camera and serum measurements of ten patients with metastasizing neuroendocrine tumors were conducted using (111)In-DTPAOC. The most suitable model was selected using the corrected Akaike information criterion. Based on that model and the estimated individual parameters, predicted and measured (90)Y-DOTATATE excretions during therapy were compared. The residence times for the pretherapeutic (measured) and therapeutic scenarios (simulated) were calculated.

RESULTS

Predicted and measured therapeutic excretion differed in three patients by 10%, 31%, and 7%. The measured pretherapeutic and therapeutic excretion differed by 53%, 56%, and 52%. The simulated therapeutic residence times of kidney and tumor were 3.1 ± 0.6 and 2.5 ± 1.2 fold higher than the measured pretherapeutic ones.

CONCLUSIONS

To avoid the introduction of unnecessary inaccuracy in dosimetry, using the same substance along with the same amount for pretherapeutic measurements and therapy is recommended.

Novel transplant strategies in adults with acute leukemia

Autologous and allogeneic hematopoietic cell transplantation (HCT) is regularly used as a curative treatment option for patients with various disorders, including acute leukemia in adults. The past decade has witnessed dramatic improvements in the reduction of treatment-related mortality (TRM), in part attributable to improved supportive care but also due to better graft selection and donor-to-recipient matching regimens, and the emergence of reduced-intensity conditioning in place of myeloablative conditioning. Despite these advances, HCT remains plagued by the risk of relapse or failure due to graft-versus-host disease, infectious complications, and TRM. This article reviews new approaches that may improve overall patient outcome.

Optimal preloading in radioimmunotherapy with anti-cD45 antibody

PURPOSE

Anti-CD45 antibody is predominantly used in the treatment of acute leukemia. CD45 is stably expressed on all leukocytes and their precursors, and therefore the liver and spleen constitute major antigen sinks. Thus, as the red marrow is the target organ, in radioimmunotherapy with anti-CD45 antibody, preloading with unlabeled antibody is a method to increase the absorbed dose to the target cells. In a previous study, a method to individually determine the optimal preload for five patients with acute leukemia was developed. Here, this method is examined and improved using two pretherapeutic measurement series and a refined pharmacokinetic model.

METHODS

To obtain the biodistribution of 111In-labeled anti-CD45 antibody under different saturation conditions, two measurement series one with and one without preloading were conducted in five patients. For each patient, two physiologically based pharmacokinetic models were fitted to the data and the corrected Akaike information criterion was used to identify the model, which was empirically most supported. The resultant parameter values were compared to values reported in the literature. To individually determine the optimal amount of unlabeled antibody for therapy, computer simulations for preloads ranging from 0 to 60 mg were performed based on the estimated parameters of each patient. The prediction power of the model was assessed by comparing the simulated therapeutic serum curves to the actual 90Y measurements.

RESULTS

Visual inspection showed good fits and the adjusted R2 was >0.90 for all patients. All parameters were in a physiologically reasonable range. The relative deviation of the predicted area under the therapeutic serum curve and the measured curve was 15%-33%. The optimal preloading increased the marrow-over-liver selectivity up to 3.9 fold compared to the simulated biodistribution using a standard dose (0.5 mg/kg).

CONCLUSIONS

The presented method can be used to individually determine the optimal preload and the corresponding residence times in radioimmunotherapy with anti-CD45 antibody.

From target selection to the minimum acceptable biological effect level for human study: use of mechanism-based PK/PD modeling to design safe and efficacious biologics

In this paper, two applications of mechanism-based modeling are presented with their utility from candidate selection to first-in-human dosage selection. The first example is for a monoclonal antibody against a cytomegalovirus glycoprotein complex, which involves an antibody binding model and a viral load model. The model was used as part of a feasibility analysis prior to antibody generation, setting the specifications for the affinity needed to achieve a desired level of clinical efficacy. The second example is a pharmacokinetic-pharmacodynamic model based on a single-dose pharmacology study in cynomolgus monkey using data on pharmacokinetics, receptor occupancy, and the dynamics of target cell depletion and recovery. The model was used to estimate the MABEL, here defined as the minimum acceptable biological effect level against which a dose is selected for a first-in-human study. From these applications, we demonstrate that mechanism-based PK/PD binding models are useful for predicting human response to biologics compounds. Especially, such models have the ability to integrate preclinical and clinical, in vitro and in vivo information and facilitate rational decision making during various stages of drug discovery and translational research.

Potential of optimal preloading in anti-CD20 antibody radioimmunotherapy: an investigation based on pharmacokinetic modeling

Recently, it has been suggested that the concept of preloading is limited by using a standard amount of unlabeled antibody. To identify the potential of optimal preloading, a pharmacokinetic model that describes the biodistribution of anti-CD20 antibody was developed. Simulations were conducted for different tumor burdens, spleen sizes, and tumor permeabilities. The optimal amount of unlabeled antibody was determined for each scenario. These simulations show that the currently administered standard amount is not optimal. A preload of 150 mg or lower would result in equal or higher tumor uptake in all cases. For tumors with high permeability, the uptake of labeled antibody could be increased by a factor of 8.5 using the considerably reduced optimal preload. The most sensitive parameter for the choice of the optimal amount of unlabeled antibody is the tumor uptake index. The results indicate that a personalized approach for radioimmunotherapy (RIT) with anti-CD20 antibody is required to account for the interpatient variability. The optimal amount of unlabeled antibody, which has to be determined by using a pharmacokinetic model, could substantially improve tumor uptake and thus RIT with anti-CD20 antibody.

Radioimmunotherapy with anti-CD66 antibody: improving the biodistribution using a physiologically based pharmacokinetic model

To improve radioimmunotherapy with anti-CD66 antibody, a physiologically based pharmacokinetic (PBPK) model was developed that was capable of describing the biodistribution and extrapolating between different doses of anti-CD66 antibody.

METHODS

The biodistribution of the (111)In-labeled anti-CD66 antibody of 8 patients with acute leukemia was measured. The data were fitted to 2 PBPK models. Model A incorporated effective values for antibody binding, and model B explicitly described mono- and bivalent binding. The best model was selected using the corrected Akaike information criterion. The predictive power of the model was validated comparing simulations and (90)Y-anti-CD66 serum measurements. The amount of antibody (range, 0.1-4 mg) leading to the most favorable therapeutic distribution was determined using simulations.

RESULTS

Model B was better supported by the data. The fits of the selected model were good (adjusted R(2) > 0.91), and the estimated parameters were in a physiologically reasonable range. The median deviation of the predicted and measured (90)Y-anti-CD66 serum concentration values and the residence times were 24% (range, 17%-31%) and 9% (range, 1%-64%), respectively. The validated model predicted considerably different biodistributions for dosimetry and therapeutic settings. The smallest (0.1 mg) simulated amount of antibody resulted in the most favorable therapeutic biodistribution.

CONCLUSION

The developed model is capable of adequately describing the anti-CD66 antibody biodistribution and accurately predicting the time-activity serum curve of (90)Y-anti-CD66 antibody and the therapeutic serum residence time. Simulations indicate that an improvement of radioimmunotherapy with anti-CD66 antibody is achievable by reducing the amount of administered antibody; for example, the residence time of the red marrow could be increased by a factor of 1.9 +/- 0.3 using 0.27 mg of anti-CD66 antibody.