scholarly journals A curative combination therapy for lymphomas achieves high fractional cell killing through low cross-resistance and drug additivity but not synergy

2018 ◽  
Author(s):  
Adam C Palmer ◽  
Christopher Chidley ◽  
Peter K Sorger
Keyword(s):  
Combination Therapy ◽  
Drug Combinations ◽  
Lessons Learned ◽  
Synergistic Interaction ◽  
Cross Resistance ◽  
Cancer Therapies ◽  
Pharmacological Interaction ◽  
Mechanistic Basis ◽  
Effective Drugs ◽  
Fractional Cell

SUMMARYCurative cancer therapies are uncommon and nearly always involve multi-drug combinations developed by experimentation in humans; unfortunately, the mechanistic basis for the success of such combinations has rarely been investigated in detail, obscuring lessons learned. Here we use isobologram analysis to score pharmacological interaction, and clone tracing and CRISPR screening to measure cross-resistance among the five drugs comprising R-CHOP, a combination therapy that frequently cures Diffuse Large B-Cell Lymphomas. We find that drugs in R-CHOP exhibit very low cross-resistance but not synergistic interaction; together they achieve a greater fractional kill according to the null hypothesis for both the Loewe dose-additivity model and the Bliss effect-independence model. These data provide direct evidence for the 50-year old hypothesis that a curative cancer therapy can be constructed on the basis of independently effective drugs having non-overlapping mechanisms of resistance, without synergistic interaction, which has immediate significance for the design of new drug combinations.

scholarly journals A curative combination cancer therapy achieves high fractional cell killing through low cross-resistance and drug additivity

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Adam C Palmer ◽  
Christopher Chidley ◽  
Peter K Sorger
Keyword(s):  
Cancer Therapy ◽  
Drug Combinations ◽  
Lessons Learned ◽  
Synergistic Interaction ◽  
Cross Resistance ◽  
Cancer Therapies ◽  
Pharmacological Interaction ◽  
Combination Cancer Therapy ◽  
Mechanistic Basis ◽  
Effective Drugs

Curative cancer therapies are uncommon and nearly always involve multi-drug combinations developed by experimentation in humans; unfortunately, the mechanistic basis for the success of such combinations has rarely been investigated in detail, obscuring lessons learned. Here, we use isobologram analysis to score pharmacological interaction, and clone tracing and CRISPR screening to measure cross-resistance among the five drugs comprising R-CHOP, a combination therapy that frequently cures Diffuse Large B-Cell Lymphomas. We find that drugs in R-CHOP exhibit very low cross-resistance but not synergistic interaction: together they achieve a greater fractional kill according to the null hypothesis for both the Loewe dose-additivity model and the Bliss effect-independence model. These data provide direct evidence for the 50 year old hypothesis that a curative cancer therapy can be constructed on the basis of independently effective drugs having non-overlapping mechanisms of resistance, without synergistic interaction, which has immediate significance for the design of new drug combinations.

scholarly journals Deploying triple artemisinin-based combination therapy (TACT) for malaria treatment in Africa: ethical and practical considerations

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Paulina Tindana ◽  
Freek de Haan ◽  
Chanaki Amaratunga ◽  
Mehul Dhorda ◽  
Rob W. van der Pluijm ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Combination Therapy ◽  
Southeast Asia ◽  
Malaria Control ◽  
Lessons Learned ◽  
Line Treatment ◽  
African Continent ◽  
First Line ◽  
First Line Treatment ◽  
Made In

AbstractMalaria remains a major cause of morbidity and mortality in Africa, particularly in children under five years of age. Availability of effective anti-malarial drug treatment is a cornerstone for malaria control and eventual malaria elimination. Artemisinin-based combination therapy (ACT) is worldwide the first-line treatment for uncomplicated falciparum malaria, but the ACT drugs are starting to fail in Southeast Asia because of drug resistance. Resistance to artemisinins and their partner drugs could spread from Southeast Asia to Africa or emerge locally, jeopardizing the progress made in malaria control with the increasing deployment of ACT in Africa. The development of triple artemisinin-based combination therapy (TACT) could contribute to mitigating the risks of artemisinin and partner drug resistance on the African continent. However, there are pertinent ethical and practical issues that ought to be taken into consideration. In this paper, the most important ethical tensions, some implementation practicalities and preliminary thoughts on addressing them are discussed. The discussion draws upon data from randomized clinical studies using TACT combined with ethical principles, published literature and lessons learned from the introduction of artemisinin-based combinations in African markets.

scholarly journals Trends in Phase II Trials for Cancer Therapies

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 178
Author(s):  
Faruque Azam ◽  
Alexei Vazquez
Keyword(s):  
Phase Ii ◽  
Null Model ◽  
Surrogate Endpoint ◽  
Response Rates ◽  
Drug Combinations ◽  
Phase Iii ◽  
Cancer Drug ◽  
Cancer Therapies ◽  
Targeted Agents ◽  
Phase Ii Trials

Background: Drug combinations are the standard of care in cancer treatment. Identifying effective cancer drug combinations has become more challenging because of the increasing number of drugs. However, a substantial number of cancer drugs stumble at Phase III clinical trials despite exhibiting favourable efficacy in the earlier Phase. Methods: We analysed recent Phase II cancer trials comprising 2165 response rates to uncover trends in cancer therapies and used a null model of non-interacting agents to infer synergistic and antagonistic drug combinations. We compared our latest efficacy dataset with a previous dataset to assess the progress of cancer therapy. Results: Targeted therapies reach higher response rates when used in combination with cytotoxic drugs. We identify four synergistic and 10 antagonistic combinations based on the observed and expected response rates. We demonstrate that recent targeted agents have not significantly increased the response rates. Conclusions: We conclude that either we are not making progress or response rate measured by tumour shrinkage is not a reliable surrogate endpoint for the targeted agents.

scholarly journals Patient-derived models of acquired resistance can identify effective drug combinations for cancer

Science ◽  
2014 ◽  
Vol 346 (6216) ◽  
pp. 1480-1486 ◽  
Author(s):  
Adam S. Crystal ◽  
Alice T. Shaw ◽  
Lecia V. Sequist ◽  
Luc Friboulet ◽  
Matthew J. Niederst ◽  
...  
Keyword(s):  
Growth Factor ◽  
Kinase Inhibitors ◽  
Acquired Resistance ◽  
Growth Factor Receptor ◽  
Drug Combinations ◽  
Effective Drug ◽  
Cancer Therapies ◽  
Lung Cancer Patients ◽  
Anaplastic Lymphoma ◽  
Culture Models

Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MAPK kinase (MEK) inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and fibroblast growth factor receptor (FGFR) inhibitors was active in an EGFR mutant resistant cancer with a mutation in FGFR3. Combined ALK and SRC (pp60c-src) inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.

scholarly journals The IDentif.AI 2.0 Pandemic Readiness Platform: Rapid Prioritization of Optimized COVID-19 Combination Therapy Regimens

2021 ◽  
Author(s):  
Agata Blasiak ◽  
Anh TL Truong ◽  
Alexandria Remus ◽  
Lissa Hooi ◽  
Shirley Gek Kheng Seah ◽  
...  
Keyword(s):  
Combination Therapy ◽  
Drug Efficacy ◽  
Drug Combinations ◽  
Multiple Drug ◽  
Original Strain ◽  
Live Virus ◽  
Drug Synergy ◽  
Positive Treatment ◽  
Strong Candidate ◽  
Combination Regimens

Objectives: We aimed to harness IDentif.AI 2.0, a clinically actionable AI platform to rapidly pinpoint and prioritize optimal combination therapy regimens against COVID-19. Methods: A pool of starting candidate therapies was developed in collaboration with a community of infectious disease clinicians and included EIDD-1931 (metabolite of EIDD-2801), baricitinib, ebselen, selinexor, masitinib, nafamostat mesylate, telaprevir (VX-950), SN-38 (metabolite of irinotecan), imatinib mesylate, remdesivir, lopinavir, and ritonavir. Following the initial drug pool assessment, a focused, 6-drug pool was interrogated at 3 dosing levels per drug representing nearly 10,000 possible combination regimens. IDentif.AI 2.0 paired prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus (propagated, original strain and B.1.351 variant) and Vero E6 assay with a quadratic optimization workflow. Results: Within 3 weeks, IDentif.AI 2.0 realized a list of combination regimens, ranked by efficacy, for clinical go/no-go regimen recommendations. IDentif.AI 2.0 revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived. Conclusions: IDentif.AI 2.0 rapidly revealed promising drug combinations for a clinical translation. It pinpointed dose-dependent drug synergy behavior to play a role in trial design and realizing positive treatment outcomes. IDentif.AI 2.0 represents an actionable path towards rapidly optimizing combination therapy following pandemic emergence.

scholarly journals Secukinumab Loss of Efficacy Is Perfectly Counteracted by the Introduction of Combination Therapy (Rescue Therapy): Data from a Multicenter Real-Life Study in a Cohort of Italian Psoriatic Patients That Avoided Secukinumab Switching

2022 ◽  
Vol 15 (1) ◽  
pp. 95
Author(s):  
Giovanni Damiani ◽  
Giulia Odorici ◽  
Alessia Pacifico ◽  
Aldo Morrone ◽  
Rosalynn R. Z. Conic ◽  
...  
Keyword(s):  
Combination Therapy ◽  
Rescue Therapy ◽  
Therapeutic Option ◽  
Real Life ◽  
Chronic Inflammatory Disease ◽  
Life Study ◽  
Secondary Failure ◽  
The Moment ◽  
Effective Drugs

Since psoriasis (PsO) is a chronic inflammatory disease, patients may experience a drug failure also with very effective drugs (i.e., secukinumab) and, consequently, dermatologists have two therapeutic options: switching or perform a combination therapy (rescue therapy) to save the drug that had decreased its efficacy. At the moment no studies focused on combination/rescue therapy of secukinumab, so we performed a 52-weeks multicenter retrospective observational study that involved 40 subjects with plaque psoriasis that experienced a secondary failure and were treated with combination therapy (ciclosporin (n = 11), MTX (n = 15), NB-UVB (n = 7) and apremilast (n = 7)). After 16 weeks of rescue/combination therapy, PASI and a DLQI varied respectively from 8 [7.0–9.0] and 13 [12.0–15.0], to 3 [2.8–4.0] and 3 [2.0–3.3]), suggesting a significant improvement of daily functionality and quality of life. Results were maintained at 52 weeks. No side effects were experienced during the study. Secukinumab remains a safety and effective drug for PsO patients also in the IL-23 and JAK inhibitors era. The rescue therapy is a valid therapeutic option in case of secukinumab secondary failure.

scholarly journals Evaluation of reverse transcriptase and protease inhibitors in two-drug combinations against human immunodeficiency virus replication.

1996 ◽  
Vol 40 (6) ◽  
pp. 1346-1351 ◽  
Author(s):  
C A Deminie ◽  
C M Bechtold ◽  
D Stock ◽  
M Alam ◽  
F Djang ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Combination Therapy ◽  
Protease Inhibitor ◽  
Reverse Transcriptase ◽  
Protease Inhibitors ◽  
Nucleoside Analogs ◽  
Drug Combinations ◽  
Hiv Protease ◽  
Human Immunodeficiency Virus Replication ◽  
Immunodeficiency Virus

Current treatments for human immunodeficiency virus (HIV) include both reverse transcriptase and protease inhibitors. Results from in vitro and clinical studies suggest that combination therapy can be more effective than single drugs in reducing viral burden. To evaluate compounds for combination therapy, stavudine (d4T), didanosine (ddI), or BMS-186,318, an HIV protease inhibitor, were combined with other clinically relevant compounds and tested in a T-cell line (CEM-SS) that was infected with HIV-RF or in peripheral blood mononuclear cells infected with a clinical HIV isolate. The combined drug effects were analyzed by the methods described by Chou and Talalay (Adv. Enzyme Regul. 22:27-55, 1984) as well as by Prichard et al. (Antimicrob. Agents Chemother. 37:540-545, 1993). The results showed that combining two nucleoside analogs (d4T-ddI, d4T-zidovudine [AZT], and d4T-zalcitabine [ddC]), two HIV protease inhibitors (BMS-186,318-saquinavir, BMS-186,318-SC-52151, and BMS-186,318-MK-639) or a reverse transcriptase and a protease inhibitor (BMS-186,318-d4T, BMS-186,318-ddI, BMS-186,318-AZT, d4T-saquinavir, d4T-MK-639, and ddI-MK-639) yielded additive to synergistic antiviral effects. In general, analysis of data by either method gave consistent results. In addition, combined antiviral treatments involving nucleoside analogs gave slightly different outcomes in the two cell types, presumably because of a difference in phosphorylation patterns. Importantly, no strong antagonism was observed with the drug combinations studied. These data should provide useful information for the design of clinical trials of combined chemotherapy.

scholarly journals Molecular Basis for Increased Susceptibility of Isolates with Atazanavir Resistance-Conferring Substitution I50L to Other Protease Inhibitors

2005 ◽  
Vol 49 (9) ◽  
pp. 3825-3832 ◽  
Author(s):  
Joseph Yanchunas ◽  
David R. Langley ◽  
Li Tao ◽  
Ronald E. Rose ◽  
Jacques Friborg ◽  
...  
Keyword(s):  
Protease Inhibitor ◽  
Protease Inhibitors ◽  
Hiv Protease ◽  
Cross Resistance ◽  
Titration Calorimetry ◽  
Binding Affinities ◽  
The Novel ◽  
Immunodeficiency Virus ◽  
Effective Drugs ◽  
Hiv 1

ABSTRACT Protease inhibitors (PIs) are highly effective drugs against the human immunodeficiency virus (HIV), yet long-term therapeutic use is limited by emergence of HIV type 1 (HIV-1) protease substitutions that confer cross-resistance to multiple protease inhibitor drugs. Atazanavir is a highly potent HIV protease inhibitor with a distinct resistance profile that includes effectiveness against most HIV-1 isolates resistant to one or two PIs. The signature resistance substitution for atazanavir is I50L, and it is frequently (53%) accompanied by a compensatory A71V substitution that helps restore viability and increases atazanavir resistance levels. We measured the binding affinities of wild-type (WT) and I50L/A71V HIV-1 proteases to atazanavir and other currently approved PIs (ritonavir, lopinavir, saquinavir, nelfinavir, indinavir, and amprenavir) by isothermal titration calorimetry. Remarkably, we find that all of the PIs have 2- to 10-fold increased affinities for I50L/A71V protease, except for atazanavir. The results are also manifested by thermal stability measures of affinity for WT and I50L/A71V proteases. Additional biophysical and enzyme kinetics experiments show I50L/A71V protease is a stable enzyme with catalytic activity that is slightly reduced (34%) relative to the WT. Computational modeling reveals that the unique resistance phenotype of I50L/A71V protease likely originates from bulky tert-butyl groups at P2 and P2′ (specific to atazanavir) that sterically clash with methyl groups on residue L50. The results of this study provide a molecular understanding of the novel hypersusceptibility of atazanavir-resistant I50L/A71V-containing clinical isolates to other currently approved PIs.

scholarly journals A Hadoop-Based Method to Predict Potential Effective Drug Combination

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yifan Sun ◽  
Yi Xiong ◽  
Qian Xu ◽  
Dongqing Wei
Keyword(s):  
Programming Model ◽  
Drug Combinations ◽  
Prediction Algorithm ◽  
Support Vector ◽  
Vector Machines ◽  
Combination Drugs ◽  
Combination Number ◽  
Multiple Drugs ◽  
Effective Drugs ◽  
Processing Steps

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request.

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