Witteles, Ronald

Abstract The therapeutic landscape for systemic immunoglobulin light chain (AL) amyloidosis has been revolutionized by daratumumab-based regimens, achieving 76% 5-year overall survival in the landmark ANDROMEDA trial. However, the current prognostic models were developed using patient populations treated with now-suboptimal therapies, creating a critical gap between risk stratification models and contemporary outcomes. This comprehensive review analyzes prognostic factors and progression biomarkers in AL, categorizing them into disease-specific (clone-related and organ-related) and patient-specific factors. Notably, traditional baseline biomarkers including difference between involved and uninvolved free light chains and bone marrow plasma cell burden are losing prognostic significance with effective clone-directed therapies. Emerging approaches show promise, including dynamic markers such as minimal residual disease by free light chain mass spectrometry, cardiac imaging parameters such as global longitudinal strain, and functional measures. There is an urgent need for validation studies and prognostic model refinement to identify patients at high risk who may benefit from interventions beyond anti–plasma cell therapy.

Importance Transthyretin amyloid cardiomyopathy (ATTR-CM) is underdiagnosed despite expanding treatment options. Objective To develop and evaluate an artificial intelligence (AI)–augmented clinical program for ATTR-CM detection. Design, Setting, and Participants This nonrandomized clinical trial involved constructing an AI model, ATTRACTnet, using electrocardiogram waveforms, echocardiographic measurements, demographics, and diagnosis codes for orthopedic manifestations of amyloidosis. A single-system, multisite, single-arm, open-label trial was conducted to evaluate its real-world performance. The model was trained and validated at a large academic referral site for ATTR-CM with external validation at an academic site. The trial was conducted as a single-system, multisite trial. Patients with left ventricular (LV) wall thickness 12 mm or more and an ATTRACTnet score 0.5 or higher were eligible. Exclusions included prior ATTR-CM testing, hypertrophic cardiomyopathy, expected life span less than 1 year, nursing home residence, advanced dementia, or LV wall thickness less than 14 mm explained by uncontrolled hypertension or moderate/severe aortic stenosis. Intervention Eligible patients were notified and offered nuclear scintigraphy testing, monoclonal protein testing, and follow-up care on agreement from the treating physician. Main Outcomes and Measure The primary outcome was a diagnosis of ATTR-CM by consensus criteria. ATTR-CM testing positivity was compared with historical and contemporary controls. Results ATTRACTnet was developed in an internal test set of 799 patients (mean [SD] age, 75.1 [11.1] years; 516 [64.7%] male and 283 [35.3%] female) using 5-fold cross-validation with an additional external test set of 422 patients. It had good discrimination for ATTR-CM detection with an area under the receiver operator characteristic curve of 0.85 (5-fold cross-validation, 0.77-0.85) in the internal set and 0.82 (95% CI, .81-0.83) in the external test set with similar performance in Hispanic, non-Hispanic Black, and non-Hispanic White patients. A total of 1471 patients were identified with positive AI model scores 0.5 or more during the study period, with 256 eligible patients who met study criteria. Of these patients, 50 underwent amyloidosis testing after physician and patient approval; 24 (48%) were diagnosed with ATTR-CM, and 21 (88%) initiated treatment within 3 months. The positivity rate was more than 2.8 times higher than historical controls (15.3%; 95% CI, 13.1%-17.9%; P < .001), with an 18% relative increase in new diagnoses vs the prior year. Conclusions and Relevance AI-augmented screening may improve ATTR-CM detection and identify patients who are missed by usual care. Prospective randomized trials are needed to determine if outcomes are improved. Trial Registration ClinicalTrials.gov Identifier: NCT06469372

Nonspecific symptoms and other diagnostic challenges lead to underdiagnosis of cardiac amyloidosis (CA). Artificial intelligence (AI) could help address these challenges, but a summary of the performance of these tools is lacking. This narrative review of published literature describes the performance of AI tools that use data from ECGs and echocardiography to improve identification of CA and challenges that hinder adoption of these tools. Thirteen studies met inclusion criteria with sample sizes ranging from 50 to 2451 patients. Four studies used ECG data, 8 used echocardiography data, and 1 used both. The CA gold standard was typically defined as a CA diagnosis in an institutional or other database but the requirements for these diagnoses were heterogenous across studies, and many did not distinguish among CA subtypes. AI model development varied considerably, and only 4 studies included external validation. The ability of models to predict CA ranged from 0.71 to 1.00, sensitivity ranged from 16% to 100%, and specificity from 75% to 100%. Only 1 study reported model performance across strata of sex, age, race, and CA type. Persistent challenges to AI adoption include usability, cost, value added, electronic health record/information technology interoperability, patient‐related factors, regulation, and privacy and liability. Published studies on AI for improved identification of CA show favorable performance measures but numerous methodologic and other challenges must be addressed before these tools are more widely adopted.

Disease-modifying therapies in both light chain and transthyretin amyloidosis have improved patient functional status and survival. Conceivably, as heart failure may progress despite amyloid therapies, more patients may be considered for heart transplantation. In earlier eras, extra-cardiac amyloid deposits significantly reduced post-heart transplant patient survival and functional status compared to the non-amyloid population. In the modern era, transplant centres have reported improved outcomes in amyloidosis as patient selection has grown more stringent. Importantly, systematic candidate evaluation should assess the degree of extra-cardiac involvement, the effectiveness of disease-modifying therapies and downstream effects on patients’ nutrition and frailty. This review outlines such an overall approach while also considering that organ-specific selection criteria may vary between individual transplant centres. A methodical approach to patient evaluation will promote better understanding of the prevalence and severity of extra-cardiac disease in amyloidosis patients referred for heart transplantation and of any disparities in decision outcomes in this population.

PURPOSE Binary cardiac response assessment using cardiac biomarkers is prognostic in light chain amyloidosis. Previous studies suggested four-level cardiac responses using N-terminal prohormone of brain natiuretic peptide improves prognostic prediction. This study was designed to validate graded cardiac response criteria using N-terminal prohormone of brain natiuretic peptide/brain natiuretic peptide. PATIENTS AND METHODS This retrospective, multicenter study included patients with light chain amyloidosis who achieved at least a hematologic partial response (PR) and were evaluable for cardiac response. Four response criteria were tested on the basis of natriuretic peptide response depth: cardiac complete response (CarCR), cardiac very good partial response (CarVGPR), cardiac PR (CarPR), and cardiac no response (CarNR). Response was classified as best response and at fixed time points (6, 12, and 24 months from therapy initiation). The study primary outcome was overall survival. RESULTS 651 patients were included. Best CarCR, CarVGPR, CarPR, and CarNR were achieved in 16%, 26.4%, 22.9%, and 34.7% of patients, respectively. Patients in cardiac stage II were more likely to achieve CarCR than patients in cardiac stage IIIA and IIIB (22% v 13.5% v 3.2%; P < .001). A deeper cardiac response was associated with a longer survival (5-year overall survival 93%, 79%, 65%, and 33% for CarCR, CarVGPR, CarPR, and CarNR, respectively; P < .001). Fixed time-point analyses and time-varying covariates Cox regression analysis, to minimize survivorship bias, affirmed the independent survival advantage of deeper cardiac responses. Four-level response performed better than two-level response as early as 12 months from therapy initiation. CONCLUSION Graded cardiac response criteria allow better assessment of cardiac improvement compared with the traditional binary response system. The study re-emphasizes the importance of early diagnosis, which increases the likelihood of deep cardiac responses.

Abstract Introduction: Renal light chain (AL) amyloidosis typically manifests as proteinuria with or without renal failure and is associated with a risk of progression to renal replacement therapy (RRT). A significant reduction in circulating amyloidogenic light chain is needed to achieve a renal response. Current renal response criteria are binary defining a renal response as &gt;30% reduction in 24-h proteinuria without worsening estimated glomerular filtration rate (eGFR). Several studies suggest that greater reduction in proteinuria following successful therapy improves renal and overall survival. Methods: AL amyloidosis patients diagnosed between 2010 to 2015, achieving at least hematological partial response (hemPR) to therapy and with renal involvement (defined as 24-h non-selective proteinuria &gt;0.5 g/24-h) were included. Four predefined renal response categories were formulated based on reduction level in pretreatment 24-h proteinuria in the absence of renal progression (≥25% decrease in eGFR): renal complete response (renCR, 24-h proteinuria ≤200 mg/24-h); renal very good partial response (renVGPR, &gt;60% reduction in 24-h proteinuria); renal partial response (renPR, 31-60% reduction in 24-proteinuria); and renal no response (renNR, 30% or less reduction). Renal response was assessed at landmark (6-, 12-, and 24 months from treatment initiation) and as best renal response. Graded renal responses were assessed as predictors for time from diagnosis to RRT and overall survival. Results: Seven hundred and thirty-seven patients were included. The median age was 63. The breakdown of renal stage was: I, 34%; II, 52%; and III, 14%. Eighty percent of patients received 1 line of therapy within 12 months of their diagnosis. Bortezomib-based therapy was given to 60% of the patients; 28% received autologous stem cell transplantation (ASCT) as their first line therapy. Hematological CR was achieved in 44% of patients, followed by hematological very good partial response (38%) and hemPR (18%). RRT was required during follow-up in 15% of patients (n=108) with a median time from diagnosis to RRT of 18 (IQR 6-43) months. Twenty-eight percent of the patients died. The median follow-up of the surviving patients was 69 months (IQR 56-86). Reduction in 24-h proteinuria from baseline improved over time with a median reduction of 34%, 50% and 71% at 6-month, 12-month, and 24-months, respectively. At best response, renCR, renVGPR, renPR and renNR were achieved in 27% (n=199), 34% (n=247), 15% (n=112) and 24% (n=179) of patients, respectively. The median time to best renal response among renal responders was 17 (IQR 8-31) months, longer for renCR (23 months, IQR 10-40) compared to renVGPR (16 months, IQR 9-27) or renPR (11 months, IQR 6-19). A renal response as early as 6 months after therapy initiation was able to predict time to RRT with an increase in RRT risk with lower level of renal response at that time point (5-year RRT risk 0%, 3%, 9% and 16% for renCR, renVGPR, renPR and renNR, respectively, P&lt;0.001, Figure 1A). Prediction of risk for RRT based on renal response depth improved at 12- and 24-months (Figure 1B-C) and at best renal response (Figure 1D). Overall survival discrimination based on renal response depth was noted as early as 12 months from therapy initiation and improved with time. Renal response criteria as best response were tested in a univariate analysis and multivariable proportional hazard models for time to RRT and OS. The graded renal response criteria demonstrated an independent prognostic role for time to RRT and OS. Along with renal stage, graded renal responses were the strongest predictors for time to RRT. Conclusions: We validated new graded renal response criteria based on reduction in 24-h proteinuria. These 4-level renal response criteria highlight the importance of achieving a deep renal response to improve renal and overall survival. These findings will allow clinicians to make decisions on therapy changes or augmentation based on response depth as early as 6-months, before irreversible renal failure develops. Figure 1 Figure 1. Disclosures Palladini: Janssen Global Services: Honoraria, Other: advisory board fees; Siemens: Honoraria; Pfizer: Honoraria. Milani: Celgene: Other: Travel support; Janssen-Cilag: Honoraria. Schönland: Sanofi: Research Funding; Prothena: Honoraria, Other: Travel grants; Janssen: Honoraria, Other: Travel grants, Research Funding; Takeda: Honoraria, Other: Travel grants; Pfizer: Honoraria. Hegenbart: Akcea: Honoraria; Alnylam: Honoraria; Janssen: Consultancy, Research Funding; Prothena: Research Funding; Pfizer: Consultancy, Honoraria. Dispenzieri: Oncopeptides: Consultancy; Alnylam: Research Funding; Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kumar: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Carsgen: Research Funding; Beigene: Consultancy; Novartis: Research Funding; Bluebird Bio: Consultancy; Amgen: Consultancy, Research Funding; Roche-Genentech: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Antengene: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding. Dimopoulos: Takeda: Honoraria; Janssen: Honoraria; Beigene: Honoraria; BMS: Honoraria; Amgen: Honoraria. Liedtke: Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Alnylam: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees. Witteles: Pfizer: Honoraria, Research Funding; Alnylam: Honoraria, Research Funding; Eidos: Research Funding. Sanchorawala: Pfizer: Honoraria; Takeda: Research Funding; Celgene: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptide: Research Funding; Karyopharm: Research Funding; Sorrento: Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees, Research Funding. Landau: Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Genzyme: Honoraria. Cibeira: Celgene: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Akcea: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wechalekar: Caelum Biosciences: Other: Clinical Trial Funding; Amgen: Research Funding; Janssen: Consultancy; Celgene: Honoraria; Takeda: Honoraria; Alexion, AstraZeneca Rare Disease: Consultancy. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria.

Abstract Introduction: Binary cardiac response assessment using NT-proBNP is prognostic in light chain (AL) amyloidosis. Previous studies suggested that refining the criteria to multi-level cardiac responses improves prognostic prediction. We validate a graded cardiac response assessment tool in AL amyloidosis using NT-proBNP or BNP. Methods: In this retrospective, multicenter study AL amyloidosis patients who were diagnosed between 2010 and 2015, achieving at least a hematological partial response (PR) within 12 months of diagnosis and were evaluable for cardiac response (defined as baseline NT-proBNP &gt;650 pg/mL or BNP &gt;150 pg/mL) were included. The following response criteria were tested: cardiac complete response (carCR, nadir NT-proBNP≤350 pg/mL or BNP≤80 pg/mL); cardiac very good partial response (carVGPR, &gt;60% reduction in NT-proBNP/BNP); Cardiac PR (carPR 31-60% reduction); and cardiac non response (carNR, ≤30% reduction). Response was assessed at fixed time points (6, 12 and 24 months from therapy initiation) and at best response. The primary outcome was overall survival based on depth of cardiac response. Multivariate Cox proportional models were analyzed to determine independent prognostic factors for OS and time to cardiac progression using variables with p-value &lt;0.1 in a univariate analysis. Results: Six hundred and fifty-one patients were included. The median age was 64 years. Mayo 2004 cardiac stage II, IIIA and IIIB was present in 47.5%, 38% and 14.5% of patients, respectively (by definition, patients with Mayo stage I do not have cardiac amyloidosis evaluable for response). Seventy-six percent of patients received only one line of therapy within the initial 12 months of diagnosis. Bortezomib-based therapy was the most common (70.2% of patients) followed by autologous stem cell transplantation (ASCT) in 15.7% of patients. Hematological CR, hematological VGPR and hematological PR as best response was achieved in 38%, 39% and 23% of patients, respectively. Forty-three percent of the patients have died, with 36% of the patients dying within 5-years of diagnosis. The median follow-up of the surviving patients is 70 months (IQR 56-84). Cardiac response was evaluable using NT-proBNP in 494 patients (75.9%), BNP in 109 patients (16.7%) and both NT-proBNP and BNP in 48 patients (7.4%). The latter two were grouped together for further analysis. The median time to best cardiac response among responders was 12 months (IQR 7-21 months; 18 months for carCR, 11.5 months for carVGPR and 9.5 months for carPR). Cardiac response improved over time with a median percentage reduction in NT-proBNP/BNP compared to baseline of 15%, 37% and 54%, at 6, 12 and 24 months respectively. Cardiac responses at 6-, 12- and 24-months are depicted in Figure 1A. At best cardiac response, carCR, carVGPR, carPR and carNR were achieved in 16%, 26%, 23% and 35% of patients, respectively. Patients who achieved a carCR had lower cardiac stage at diagnosis compared to patients who achieved carVGPR or carPR (stage II 65% vs 47% vs 47%, respectively; P&lt;0.001). At least carPR at 6 and 12 months and at least carVGPR at 24-months was associated with better survival compared with a lower depth of response. At best cardiac response, deeper cardiac response was associated with a longer survival (5-year OS 93%, 80%, 62% and 35% for carCR, carVGPR, carPR and carNR, respectively; P&lt;0.001, Figure 1B). A 2-year landmark analysis (excluding early deaths not evaluable for cardiac response depth) confirmed improved survival with a deeper cardiac response (5-year OS 93%, 82%, 70% and 58%, P&lt;0.001; Figure 1C). These cardiac response criteria were independent predictors of survival and time to cardiac progression (&gt;30% rise in NT-proBNP/BNP) in multivariate analysis that included age, type of first line therapy, light chain burden, cardiac stage, and hematological response. Conclusions: We validated the prognostic value of graded cardiac response. These response criteria allow better discrimination of patient populations and assessment of treatment effectiveness in an era of improved therapies for AL amyloidosis. The study emphasizes the importance of early diagnosis which increases the likelihood of deep and durable cardiac responses. Figure 1 Figure 1. Disclosures Dispenzieri: Oncopeptides: Consultancy; Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Takeda: Research Funding; Alnylam: Research Funding; Janssen: Consultancy, Research Funding. Palladini: Siemens: Honoraria; Pfizer: Honoraria; Janssen Global Services: Honoraria, Other: advisory board fees. Schönland: Janssen: Honoraria, Other: Travel grants, Research Funding; Takeda: Honoraria, Other: Travel grants; Sanofi: Research Funding; Pfizer: Honoraria; Prothena: Honoraria, Other: Travel grants. Hegenbart: Alnylam: Honoraria; Janssen: Consultancy, Research Funding; Prothena: Research Funding; Pfizer: Consultancy, Honoraria; Akcea: Honoraria. Kumar: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Novartis: Research Funding; Merck: Research Funding; Tenebio: Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Kastritis: Genesis Pharma: Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding. Dimopoulos: Beigene: Honoraria; Takeda: Honoraria; BMS: Honoraria; Janssen: Honoraria; Amgen: Honoraria. Liedtke: GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Sanofi: Membership on an entity's Board of Directors or advisory committees; Alnylam: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees. Witteles: Eidos: Research Funding; Alnylam: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Sanchorawala: Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Proclara: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Karyopharm: Research Funding; Oncopeptide: Research Funding; Pfizer: Honoraria; Sorrento: Research Funding. Landau: Genzyme: Honoraria; Takeda: Research Funding; Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees. Cibeira: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Akcea: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board; Aurora Biopharma: Other: Stock option.