NEURAL NETWORKS IN FORECASTING AND DECISION MAKING

Neural networks (NN) have been widely touted as solving many forecasting and decision modeling problems. For example, they are argued to be able to model easily any type of parametric or non-parametric process and also automatically and optimally transform the input data. Also, they are easy to embed in information systems and they can learn how to perform simple forecasting and decision making tasks without human input. Our research-in-progress evaluates these claims. We will spend the first half of the session reviewing our work comparing neural networks to classical techniques in time series forecasting, regression-based causal forecasting, and regression-based decision models. In tile second half of the session, we will discuss the art and science of building these models. In Hill, O\u27Connor and Remus (1992), time series forecasts based on neural networks were compared with forecasts from six statistical time series methods (including exponential smoothing and Box-Jenkins) and two judgment-based methods; we did this for 111 real financial time series. The classical methods were all estimated by experts. Across all series, the neural networks did better than or as good as statistical and judgment methods. In Marquez et al. (forthcoming), data representing three common bivariate functional forms used in causal forecasting (linear, log-linear, and reciprocal) were generated and the performance of the neural network models was compared against the true regression model across differing functional forms, sample sizes, and noise levels. The results showed that neural network models perform within 2% of the mean absolute percentage error (MAPE); this is very good performance in the real world. This work is continuing as Marquez studies issues such as the vulnerability of neural networks and regression to multicolinearity, outliers, and other data problems. In Remus and Hill (forthcoming), tile production scheduling decisions as modeled by neural networks and regression-based decision rules for sixty-two decision makers were compared. Neural network models performed as well as but not better than those using the linear regression models. In Hill and Remus (forthcoming), the above research was continued and composite neural network models were estimated. The neural networks performed better than both the classical models and neural networks from the earlier study. The coinposite neural network also performed at least as well as classical composite models

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Patent valuation : improving decision making through analysis

A practical resource for valuing patents that is accessible to the complete spectrum of decision makers in the patent process. In today\u27s economy, patents tend to be the most important of the intellectual property (IP) assets. It is often the ability to create, manage, defend, and extract value from patents that can distinguish competitive success and significant wealth creation from competitive failure and economic waste. Patent Valuation enhances the utility and value of patents by providing IP managers, IP creators, attorneys, and government officials with a useable resource that allows them to use actual or implied valuations when making patent-related decisions. Involves a combination of techniques for describing patent valuation Includes descriptions of various topics, illustrative cases, step-by-step valuation techniques, user-friendly procedures and checklists, and examples Serves as a useable resource that allows IP managers to use actual or implied valuations when making patent-related decisions One of the most fundamental premises of the book is that these valuation skills can be made accessible to each of the various decision makers in the patent process. Patent Valuation involves narrative descriptions of the various topics, illustrative cases, step-by-step valuation techniques, user-friendly procedures and checklists, and an abundance of examples to demonstrate the more complex concepts

Chromosomal macrodomains and associated proteins : implications for DNA organization and replication in gram negative bacteria

The Escherichia coli chromosome is organized into four macrodomains, the function and organisation of which are poorly understood. In this review we focus on the MatP, SeqA, and SlmA proteins that have recently been identified as the first examples of factors with macrodomain-specific DNA-binding properties. In particular, we review the evidence that these factors contribute towards the control of chromosome replication and segregation by specifically targeting subregions of the genome and contributing towards their unique properties. Genome sequence analysis of multiple related bacteria, including pathogenic species, reveals that macrodomain-specific distribution of SeqA, SlmA, and MatP is conserved, suggesting common principles of chromosome organisation in these organisms. This discovery of proteins with macrodomain-specific binding properties hints that there are other proteins with similar specificity yet to be unveiled. We discuss the roles of the proteins identified to date as well as strategies that may be employed to discover new factors

H-NS promotes looped domain formation in the bacterial chromosome

SummaryThe bacterial chromosome is organized into loops, which constitute topologically isolated domains. It is unclear which proteins are responsible for the formation of the topological barriers between domains. The abundant DNA-binding histone-like nucleoid structuring protein (H-NS) is a key player in the organization and compaction of bacterial chromosomes [1,2]. The protein acts by bridging DNA duplexes [3], thus allowing for the formation of DNA loops. Here, genome-wide studies of H-NS binding suggest that this protein is directly involved in the formation or maintenance of topological domain barriers

Primary Analysis of Zuma-5: A Phase 2 Study of Axicabtagene Ciloleucel (Axi-Cel) in Patients with Relapsed/Refractory (R/R) Indolent Non-Hodgkin Lymphoma (iNHL)

Background: Patients with advanced-stage iNHL, including follicular lymphoma (FL) and marginal zone lymphoma (MZL), frequently relapse with standard treatment, underscoring a need for novel therapies. Axi-cel autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy is approved for the treatment of R/R large B cell lymphoma after ≥ 2 lines of systemic therapy. Here, we present the primary analysis of ZUMA-5, a Phase 2, multicenter, single-arm study of axi-cel in patients with R/R iNHL. Methods: Adults with FL (Grades 1-3a) or MZL (nodal or extranodal) had R/R disease after ≥ 2 lines of therapy (must include an anti-CD20 mAb plus an alkylating agent), and ECOG 0 - 1. Patients underwent leukapheresis followed by conditioning therapy (cyclophosphamide/fludarabine) and a single infusion of axi-cel at 2 × 106 CAR T cells/kg. The primary endpoint was objective response rate (ORR) by central review (per Lugano classification; Cheson, et al. J Clin Oncol. 2014). Secondary endpoints included complete response (CR) rate, duration of response (DOR), progression-free survival (PFS), overall survival (OS), incidence of adverse events (AEs), and levels of CAR T cells in blood and cytokines in serum. The primary efficacy analysis occurred when ≥ 80 treated patients with FL had ≥ 12-months follow-up. Results: As of 3/12/2020, 146 patients with iNHL (124 FL; 22 MZL) received axi-cel; 84 patients with FL had ≥ 12-months follow-up. The median age was 61 years (range, 34 - 79); 57% of patients were male. Thirty-eight percent of patients had ECOG 1, 86% had stage III/IV disease, 47% had ≥ 3 FLIPI, and 49% had high tumor bulk (GELF). Patients had a median 3 prior lines of therapy (range, 1 - 10); 64% had ≥ 3 prior lines. Progression < 2 years after initial chemoimmunotherapy (POD24) occurred in 55% of patients, and 68% were refractory to last prior treatment. Axi-cel was successfully manufactured for all enrolled patients. With a median follow-up of 17.5 months (range, 1.4 - 31.6), the ORR was 92% among efficacy-evaluable patients with iNHL (n = 104), with a 76% CR rate. In patients with FL (n = 84), the ORR was 94% (80% CR rate); in those with MZL (n = 20), the ORR was 85% (60% CR rate). ORR was comparable across key risk groups analyzed by FLIPI, POD24, GELF, refractory status, and prior lines of therapy. As of the data cutoff, 62% of all treated patients had ongoing responses (64% for FL). The medians for DOR, PFS, and OS were not reached; 12-month estimated rates were 72% (95% CI, 61 - 80), 74% (95% CI, 63 - 82), and 93% (95% CI, 86 - 97), respectively. AEs of any grade occurred in 99% of all treated patients. Grade ≥ 3 AEs occurred in 86% of patients with iNHL (85% in FL; 95% in MZL), most commonly neutropenia (33%), decreased neutrophil count (27%), and anemia (23%). Grade ≥ 3 cytokine release syndrome (CRS; per Lee, et al, Blood. 2014) occurred in 7% of patients with iNHL (6% in FL; 9% in MZL). Grade ≥ 3 neurologic events (NEs; per CTCAE v4.03) occurred in 19% of patients with iNHL (15% in FL; 41% in MZL). Most CRS (118/119) and NEs (81/87) of any grade resolved by data cutoff. Grade 5 AEs occurred in 3 patients: multisystem organ failure in the context of CRS (Day 7; related to axi-cel; n = 1 FL), aortic dissection (Day 399; unrelated to axi-cel; n = 1 FL), and coccidioidomycosis infection (Day 327; unrelated to axi-cel; n = 1 MZL). The median peak CAR T cell level was 38 cells/µL (range, 0 - 1415) in all treated patients with iNHL, with 36 cells/µL (range, 0 - 1415) in those with FL and 53 cells/µL (range, 2 - 453) in those with MZL. The AUC0 - 28 was 448 cells/µL × days (range, 6 - 19,900) in all treated patients with iNHL, with 422 cells/µL × days (range, 6 - 19,900) and 552 cells/µL × days (range, 13 - 6468) in those with FL and MZL, respectively. The median time to peak was 9 days (range, 8 - 371) in all patients, 8 days (range, 8 - 371) in patients with FL, and 15 days (range, 8 - 29) in patients with MZL. In efficacy-evaluable patients with FL, median peak CAR T cell levels were numerically greater in those with ongoing response at 12 months than in those who relapsed (P = .057). In all treated patients with FL, CAR T cell peak was associated with Grade ≥ 3 CRS (P = .031) and NEs (P = .005). Conclusions: Axi-cel had considerable and durable clinical benefit in patients with iNHL, with high ORR and CR rates. Axi-cel had a manageable safety profile, with lower rates of Grade ≥ 3 NEs observed in patients with FL vs those in patients with MZL and those previously reported in aggressive NHL (Locke, et al. Lancet Oncol. 2019). Disclosures Chavez: Genentech: Speakers Bureau; Epizyme: Speakers Bureau; Gilead: Consultancy; Verastem: Consultancy; Novartis: Consultancy; Kite, a Gilead Company: Consultancy, Speakers Bureau; Pfizer: Consultancy; Celgene: Consultancy; AstraZeneca: Speakers Bureau; Morphosys: Consultancy, Speakers Bureau; Merck: Research Funding; Bayer: Consultancy; BeiGene: Speakers Bureau; Karyopharm: Consultancy; AbbVie: Consultancy. Sehgal:Juno Therapeutics: Research Funding; TP Therapeutics: Research Funding; Prothena: Research Funding; Gilead Sciences: Research Funding; Bristol-Myers Squibb: Research Funding; Merck: Research Funding. William:Celgene: Consultancy, Honoraria; Incyte: Research Funding; Seattle Genetics: Research Funding; Merck: Research Funding; Dova: Research Funding; Guidepoint Global: Consultancy; Kyowa Kirin: Consultancy, Honoraria. Munoz:Incyte: Research Funding; Fosunkite: Consultancy; Innovent: Consultancy; Acrotech/Aurobindo: Speakers Bureau; Verastem: Speakers Bureau; AstraZeneca: Speakers Bureau; Genentech/Roche: Research Funding, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; Kyowa: Consultancy, Honoraria, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Bayer: Consultancy, Research Funding, Speakers Bureau; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy; Janssen: Consultancy, Research Funding, Speakers Bureau; Juno/Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; Alexion: Consultancy; Beigene: Consultancy, Speakers Bureau; Merck: Research Funding; Portola: Research Funding; Millenium: Research Funding. Salles:BMS/Celgene: Honoraria, Other: consultancy or advisory role; Kite, a Gilead Company: Honoraria, Other: consultancy or advisory role ; Epizyme: Honoraria, Other: consultancy or advisory role; Janssen: Honoraria, Other: consultancy or advisory role; MorphoSys: Honoraria, Other: consultancy or advisory role; Novartis: Honoraria, Other: consultancy or advisory role; Roche: Honoraria, Other: consultancy or advisory role; Abbvie: Other: consultancy or advisory role; Autolos: Other: consultancy or advisory role; Debiopharm: Consultancy, Honoraria, Other: consultancy or advisory role; Genmab: Honoraria, Other; Karyopharm: Honoraria; Takeda: Honoraria. Munshi:Kite, a Gilead Company: Honoraria, Speakers Bureau; Incyte: Honoraria, Speakers Bureau. Maloney:Celgene: Consultancy, Honoraria, Research Funding; Bioline Rx: Consultancy, Honoraria; Juno Therapeutics: Consultancy, Honoraria, Patents & Royalties, Research Funding; Gilead Science: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; A2 Biotherapeutics: Consultancy, Current equity holder in publicly-traded company, Honoraria; Genentech: Consultancy, Honoraria. de Vos:Bayer: Consultancy; Verastem: Consultancy. Reshef:Kiadis: Research Funding; Monsanto: Consultancy; Novartis: Honoraria; Magenta: Consultancy; Atara: Consultancy, Research Funding; Celgene: Consultancy; Bristol-Myers Squibb: Research Funding; Takeda: Research Funding; Incyte: Research Funding; Pharmacyclics: Research Funding; Immatics: Research Funding; Shire: Research Funding; Bluebird: Research Funding; Gilead: Consultancy, Honoraria, Other: Travel support, Research Funding. Leslie:Epizyme: Honoraria, Speakers Bureau; Karyopharm: Honoraria, Speakers Bureau; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; ADC therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Speakers Bureau; BMS: Speakers Bureau; KitePharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BeiGene: Honoraria, Speakers Bureau; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Yakoub-Agha:Celgene: Honoraria; Novartis: Honoraria; Gilead/Kite: Honoraria, Other: travel support; Janssen: Honoraria; Jazz Pharmaceuticals: Honoraria. Oluwole:Bayer: Consultancy; Spectrum Pharmaceuticals: Consultancy; Pfizer: Consultancy; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding. Fung:AstraZeneca: Honoraria, Other: speakers' bureau, travel support; Genentech: Honoraria, Other: speakers' bureau, travel support; AbbVie: Honoraria, Other: speakers' bureau, travel support; Kite, a Gilead Company: Honoraria, Other: speakers' bureau, travel support; Sanotif: Honoraria, Other: speakers' bureau, travel support; Takeda: Honoraria, Other: speakers' bureau, travel support; Janssen Oncology: Honoraria, Other: speakers' bureau, travel support. Rosenblatt:Merck: Other: consultancy or advisory role ; Biograph55: Other: consultancy or advisory role, Research Funding; Synergy: Patents & Royalties; University of Miami: Ot

Axicabtagene ciloleucel in relapsed or refractory indolent non-Hodgkin lymphoma (ZUMA-5): a single-arm, multicentre, phase 2 trial

Most patients with advanced-stage indolent non-Hodgkin lymphoma have multiple relapses. We assessed axicabtagene ciloleucel autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy in relapsed or refractory indolent non-Hodgkin lymphoma. ZUMA-5 is a single-arm, multicentre, phase 2 trial being conducted at 15 medical cancer centres in the USA and two medical cancer centres in France. Patients were eligible if they were aged 18 years or older, with histologically confirmed indolent non-Hodgkin lymphoma (follicular lymphoma or marginal zone lymphoma), had relapsed or refractory disease, previously had two or more lines of therapy (including an anti-CD20 monoclonal antibody with an alkylating agent), and an Eastern Cooperative Oncology Group performance score of 0 or 1. Patients underwent leukapheresis and received conditioning chemotherapy (cyclophosphamide at 500 mg/m per day and fludarabine at 30 mg/m per day on days -5, -4, and -3) followed by a single infusion of axicabtagene ciloleucel (2 × 10 CAR T cells per kg) on day 0. The primary endpoint was overall response rate (complete response and partial response) assessed by an independent review committee per Lugano classification. The primary activity analysis was done after at least 80 treated patients with follicular lymphoma had been followed up for at least 12 months after the first response assessment at week 4 after infusion. The primary analyses were done in the per-protocol population (ie, eligible patients with follicular lymphoma who had 12 months of follow-up after the first response assessment and eligible patients with marginal zone lymphoma who had at least 4 weeks of follow-up after infusion of axicabtagene ciloleucel). Safety analyses were done in patients who received an infusion of axicabtagene ciloleucel. This study is registered with ClinicalTrials.gov, NCT03105336, and is closed to accrual. Between June 20, 2017, and July 16, 2020, 153 patients were enrolled and underwent leukapheresis, and axicabtagene ciloleucel was successfully manufactured for all enrolled patients. As of data cutoff (Sept 14, 2020), 148 patients had received an infusion of axicabtagene ciloleucel (124 [84%] who had follicular lymphoma and 24 [16%] who had marginal zone lymphoma). The median follow-up for the primary analysis was 17·5 months (IQR 14·1-22·6). Among patients who were eligible for the primary analysis (n=104, of whom 84 had follicular lymphoma and 20 had marginal zone lymphoma), 96 (92%; 95% CI 85-97) had an overall response and 77 (74%) had a complete response. The most common grade 3 or worse adverse events were cytopenias (104 [70%] of 148 patients) and infections (26 [18%]). Grade 3 or worse cytokine release syndrome occurred in ten (7%) patients and grade 3 or 4 neurological events occurred in 28 (19%) patients. Serious adverse events (any grade) occurred in 74 (50%) patients. Deaths due to adverse events occurred in four (3%) patients, one of which was deemed to be treatment-related (multisystem organ failure). Axicabtagene ciloleucel showed high rates of durable responses and had a manageable safety profile in patients with relapsed or refractory indolent non-Hodgkin lymphoma. Kite, a Gilead Company