Objective: To assess the efficacy and safety of R788 (fostamatinib disodium), an inhibitor of spleen tyrosine kinase (Syk), in patients with active rheumatoid arthritis (RA) that did not respond to biologic therapies.Methods: A total of 219 patients with active RA in whom treatment with biologic agents had failed were enrolled in a 3‐month multicenter, randomized, double‐blind, placebo‐controlled trial of R788. The primary end point was the percentage of patients who met the American College of Rheumatology 20% improvement criteria (achieved an ACR20 response) at month 3. Secondary end points included changes in inflammation and damage, as assessed by magnetic resonance imaging (MRI), and changes in the Disease Activity Score.Results: The ACR20 response in the R788 100 mg twice daily group was 38%, versus 37% in the placebo group, at month 3. No significant differences were achieved in the ACR20, ACR50, or ACR70 response levels at 3 months. There were differences between the groups from baseline to month 3 in the secondary end points C‐reactive protein (CRP) level and synovitis score on MRI. There were baseline differences in steroid use, prior biologic use, and synovitis score on MRI between the R788 group and the placebo group that may have affected the outcomes. A high placebo response rate was seen in this trial, and exploratory analysis suggested that this may in part have been driven by patients who entered the trial with an elevated erythrocyte sedimentation rate but normal CRP level.Conclusion: Our findings indicate that there were no differences in the primary end point between the R788 and placebo groups. Differences were observed between the R788 and placebo groups in secondary end points, particularly in those patients who entered the study with an elevated CRP level.

Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.

The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision (P< 0.05) and strongly correlated with measured response (P < 0.01). Further, we use the model to investigate, in silico, a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients (P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.

Objectives This randomised, double-blind, placebo-controlled phase IIIb study evaluated the impact of abatacept on MRI pathology as a primary outcome in methotrexate (MTX)-refractory patients with rheumatoid arthritis. Methods Patients received intravenous abatacept (∼10 mg/kg) or placebo, on background MTX, for 4 months, followed by an 8-month open-label extension (OLE; all patients received abatacept plus MTX). Patients had 1.5T MRI with intravenous contrast at baseline, Months 4 and 12; wrist synovitis (three locations assessed), and wrist and hand (15 and eight locations assessed, respectively) osteitis and erosion were scored using OMERACT-RAMRIS. Results 26/27 abatacept- and 23/23 placebo-randomised patients completed Month 4 and entered the OLE; 26 and 21 completed Month 12. The primary endpoint was not achieved; mean change (SD) from baseline in synovitis was −0.44 (1.47) for abatacept versus 0.52 (1.38) for placebo (p=0.103) at Month 4. For mean change in synovitis adjusted for baseline score (sensitivity analysis), the difference between groups was −0.69, p=0.078. Adjusted mean changes (SE) in osteitis and erosion were −1.94 (0.86) and 0.45 (0.43) for abatacept, and 1.54 (0.90) and 0.95 (0.45) for placebo. Further MRI improvements were observed up to Month 12 for abatacept and from Months 4 to 12 for placebo-treated patients switched to abatacept at Month 4. Clinical efficacy was shown with abatacept and sustained to Month 12. Conclusions Despite small patient numbers, MRI detected structural and synovial benefit, sustained to Month 12 in abatacept+MTX-treated patients, and improvements in structural and inflammatory outcomes for placebo+MTX-treated patients following addition of abatacept. Clinical trial registration Clinicaltrials.gov NCT00420199.

Objective To examine the imaging-detected mechanism of reduction of structural joint damage progression by tocilizumab (TCZ) in patients with rheumatoid arthritis (RA) using MRI. Methods In a substudy of a randomised, double-blind, phase 3b study (ACT-RAY) of biologic-naïve patients with RA who were methotrexate (MTX)-inadequate responders, 63 patients were randomised to continue MTX or receive placebo (PBO), both in combination with TCZ 8 mg/kg every 4 weeks, with optional additional disease-modifying antirheumatic drugs at week 24 if Disease Activity Score of 28 joints < 3.2. The most symptomatic hand was imaged with 0.2 Tesla extremity MRI at weeks 0, 2, 12 and 52. MR images were scored using Outcome Measures in Rheumatology–Rheumatoid Arthritis Magnetic Resonance Imaging Score. Predictors of week 52 erosion progression were determined by logistic regression analysis. Results TCZ + PBO (n=32) demonstrated mean improvements in synovitis from baseline to weeks 2 (−0.92; p=0.0011), 12 (−1.86; p<0.0001) and 52 (−3.35; p<0.0001), while TCZ + MTX (n=31) had mean improvements in synovitis at week 12 (−0.88; p=0.0074), but not week 52 (−1.00; p=0.0711). TCZ+PBO demonstrated mean reductions in osteitis at weeks 12 (−5.10; p=0.0022) and 52 (−8.56; p=0.0006), while TCZ+MTX had mean reductions at weeks 2 (−0.21; p0.80). Baseline synovitis and worsening of osteitis predicted erosion progression. Conclusions Rapid suppression of synovitis and osteitis with reduction in structural joint damage progression occurred with TCZ, as monotherapy or in combination with MTX, through week 52.