Our rationale was to build a refined dosimetry model for 177Lu-DOTATATE in vivo experiments enabling the correlation of absorbed dose with double-strand break (DSB) induction and cell death. Methods: Somatostatin receptor type 2 expression of NCI-H69 xenografted mice, injected with 177Lu-DOTATATE, was imaged at 0, 2, 5, and 11 d. This expression was used as input to reconstruct realistic 3-dimensional heterogeneous activity distributions and tissue geometries of both cancer and heathy cells. The resulting volumetric absorbed dose rate distributions were calculated using the GATE (Geant4 Application for Tomographic Emission) Monte Carlo code and compared with homogeneous dose rate distributions. The absorbed dose (0–2 d) on micrometer-scale sections was correlated with DSB induction, measured by γH2AX foci. Moreover, the absorbed dose on larger millimeter-scale sections delivered over the whole treatment (0–14 d) was correlated to the modeled in vivo survival to determine the radiosensitivity parameters α and β for comparison with experimental data (cell death assay, volume response) and external-beam radiotherapy. The DNA-damage repair half-life Tμ and proliferation doubling time TD were obtained by fitting the DSB and tumor volume data over time. Results: A linear correlation with a slope of 0.0223 DSB/cell mGy−1 between the absorbed dose and the number of DSBs per cell has been established. The heterogeneous dose distributions differed significantly from the homogeneous dose distributions, with their corresponding average S values diverging at 11 d by up to 58%. No significant difference between modeled in vivo survival was observed in the first 5 d when using heterogeneous and uniform dose distributions. The radiosensitivity parameter analysis for the in vivo survival correlation indicated that the minimal effective dose rates for cell kill was 13.72 and 7.40 mGy/h, with an α of 0.14 and 0.264 Gy−1, respectively, and an α/β of 100 Gy; decreasing the α/β led to a decrease in the minimal effective dose rate for cell kill. Within the linear quadratic model, the best matching in vivo survival correlation (α = 0.1 Gy−1, α/β = 100 Gy, Tμ = 60 h, TD = 14.5 d) indicated a relative biological effectiveness of 0.4 in comparison to external-beam radiotherapy. Conclusion: Our results demonstrated that accurate dosimetric modeling is crucial to establishing dose–response correlations enabling optimization of treatment protocols. Targeted radionuclide therapy using β-emitting radiolabeled somatostatin analogs is currently applied to patients bearing inoperable neuroendocrine tumors that overexpress the somatostatin receptor type 2 (SSTR2) (1). Treatment options include 90Y-DOTATOC and 177Lu-DOTATATE, which is registered as Lutathera (Advanced Accelerator Applications SA). 177Lu-DOTATATE therapy has been shown to be successful for many patients, leading to markedly prolonged survival and a better quality of life than with other therapies (2,3). However, 177Lu-DOTATATE therapy is prescribed at a fixed-activity dosing scheme primarily irrespective of the patient’s weight, age, disease burden, uptake, and tumor-specific radiosensitivity (4), leading to a suboptimal but overall safe therapy. In addition, preclinical research into targeted radionuclide therapy has been marked by a scarcity of dosimetric evaluations, sound radiobiologic understanding, and absorbed dose–effect models that could predict tumor response. Nevertheless, evidence strongly implies the existence of an absorbed dose–effect relationship (5), which might be used to guide personalized treatment for an optimized therapeutic approach. Historically, tumor response to targeted radionuclide therapy has been related to macroscopic quantities such as whole-tumor absorbed dose, assuming uniform distribution of the internalized radionuclide and, hence, uniform energy deposition (6). However, the biologic response among cells within a tumor can vary greatly, depending on the spatial heterogeneity of dose distributions at multicellular, cellular, and subcellular levels (7,8). The knowledge of individual cellular absorbed doses and dose rates, together with their radiation sensitivity (α, β), sublethal damage repair, and repopulation capacity, is theoretically indispensable to assess the capability of the treatment to kill every tumor cell, thus impairing tumor regrowth. At present, few studies have shown that tumor SSTR2 expression status can be associated with clinical outcome (9,10), and a more recent study has addressed the correlation between SSTR2 levels and DNA double-strand break (DSB) formation at a preclinical level (11). Here, we used SSTR2 levels as inputs to model tumor (cancer/healthy cells) and activity heterogeneity on a cellular scale. The resulting absorbed dose and dose rate calculations were used to determine absorbed dose–effect relationships on both a nanoscale (DNA DSBs) and a macroscale (in vivo tumorous cell survival).