Innovation in Oncology Drug Development

Validation of the Cancer-Specific Preference-Based Measure EORTC QLU-C10D against the Generic Instruments EQ-5D-5L and SF-6Dv2 in a Prospectively Collected Sample of Patients with Cancer in Austria and France

BACKGROUND

The Quality of Life Utility - Core 10 Dimensions (QLU-C10D) is a disease-specific preference-based measure (PBM) designed to obtain health state utility values from patients with cancer. Previously, satisfactory psychometric properties were established from retrospective trial analyses using clinical anchors. This study aimed to validate the QLU-C10D against two generic PBMs in a prospective sample of Austrian and French patients with cancer using patient-reported anchors.

METHODS

Patients completed the European Organisation of Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire - Core 30 (QLQ-C30), EQ-5D-5L and Short Form 36 (SF-36) at study baseline (any time during anti-cancer treatment) plus a follow-up assessment 3-6 months later. Sociodemographic and clinical characteristics were assessed. QLU-C10D and SF-6Dv2 utilities were calculated from QLQ-C30 and SF-36 data, respectively. German, French and UK value sets were applied for all three PBMs. Floor and ceiling effects were assessed. Known-group validity (independent t-test) and responsiveness (paired t-tests) were assessed respectively by ability to detect health status differences and changes over time according to patient-rated overall quality of life/health perception assessed by the QLQ-C30 Global Health Status scale, the EQ-5D-5L VAS and the SF-36 General Health scale.

RESULTS

A total of 465 patients were included in the analysis. QLU-C10D index scores (intra-class correlation) and domains (Pearson) were correlated with EQ-5D-5L and Short-Form Six Dimensions (SF-6Dv2) conceptual counterparts. Correlation coefficients for the index scores of QLU-C10D and the generic PBMs ranged from 0.63 to 0.81. The QLU-C10D detected statistically significant differences between groups at baseline in 100% of tests performed (n = 27). For changes over time, QLU-C10D detected expected effects in 68% of cases (n = 29). In comparison with the generic PBMs, QLU-C10D detected differences and changes with a higher statistical efficiency in 76% of cases (77 of 102).

CONCLUSIONS

The QLU-C10D is a fit-for-purpose ready-to-use PBM to estimate health state utilities of patients with cancer. This study adds to evidence that QLU-C10D has appropriate psychometric properties and appears to have higher statistical efficiency than generic PBMs in cancer.

Editorial 15th Anniversary of Pharmaceutics-Improvement of Drug Bioavailability

Improving the health of humans and animals depends on the discovery of new active molecules as well as improving the bioavailability of molecules already marketed [...].

The Role of Real-World Data and Evidence in Oncology Medicines Approved in EU in 2018-2019

Use of Real-World data (RWD) has gained the interest of different stakeholders in cancer care. The aim of this study was to identify and describe the use of RWD/RWE during the pre-authorisation phase of products authorised by the EMA in 2018 and 2019 (n=111), with the focus on oncology medicines (n=24). Information was extracted from the European Public Assessment Report (EPAR) summaries and recorded for 5 stages (11 categories) of the drug development lifecycle (discovery, early development, clinical development, registration/market launch, lifecycle management). Specific chapters of full EPAR were reviewed to substantiate the findings on RWD/RWE use in clinical trial design, efficacy, safety, and effectiveness evaluation. RWD/RWE is present in all stages of the oncology drug development; 100.0% in discovery, 37.5% early development, 58.3% in clinical development, 62.5% in registration decision and 100.0% in post-authorization lifecycle management. Examples showed that trial design supported by RWD/RWE included use of open label/single arm studies; efficacy was about using either comparison of results to historical controls, supplying survey data obtained outside the clinical trial or utilizing expert panel advice; safety about including literature findings in evidence; and effectiveness on comparison of trial results of the given product to historical data or existing standard of care. The findings of this study provide specific insights into how RWD/RWE is used in development of cancer therapeutics, how it contributes to regulatory decision making and can guide further policy developments in this field.

Assessing Definitions and Incentives Adopted for Innovation for Pharmaceutical Products in Five High-Income Countries: A Systematic Literature Review

BACKGROUND

The concept of health care innovation varies across organizations and countries. Harmonizing the definitions of innovation can augment the discovery of new therapies, minimize costs, and streamline drug development and approval processes. A systematic literature review (SLR) was conducted to gather insights surrounding different elements of innovation in the USA, the UK, France, Germany, and Japan. The SLR identified studies that have defined innovation and captured the types of incentives provided to promote innovation.

METHODS

The MEDLINE, Embase, and EconLit databases were searched via the OVID SP platform on October 22, 2020. A secondary desk search literature review was performed to identify additional information of interest in regional languages: French, German, and Japanese. All the relevant literature in English was screened using the Linguamatics natural language processing (NLP) tool, except for articles from EconLit, which were screened manually using structured search strategies. Articles that describe a definition of innovation or refer to a definition of innovation published were included. All full-text articles were reviewed manually, and two reviewers independently screened the full texts for eligibility.

RESULTS

After screening, 90 articles were considered to meet the SLR objectives. The most common dimension of innovation identified was therapeutic benefit as a measure of innovation, followed by newness and novelty aspects of innovations. Incentives around exclusivities were found to be the most prevalent in the data set, followed by rewards and premiums. Among the different therapy areas, the largest number of innovations was targeted at oncology.

CONCLUSIONS

This SLR highlights the lack of a unified definition of innovation among regulatory authorities and health technology assessment bodies in five countries, and variation in the types of incentives associated with innovation. The targeted countries cover different dimensions of definition and incentives of innovation at varying levels, with a few focused on specific therapy areas. Harmonization and consensus for innovation would be needed across countries because drug development is a global undertaking. This SLR envisages a more holistic approach to evaluation, wherein the value provided to patients and health systems is accounted for. The results of this SLR will help to promote broader discussion among different stakeholders and decision makers across countries to identify gaps in policies and develop sustainable strategies to promote innovation for pharmaceutical products.

Liposomal amphotericin B—the future

Advances in medicine have led to a growing number of people with compromised or suppressed immune systems who are susceptible to invasive fungal infections. In particular, severe fungal infections are becoming increasingly common in ICUs, affecting people within and outside of traditional risk groups alike. This is exemplified by the emergence of severe viral pneumonia as a significant risk factor for invasive pulmonary aspergillosis, and the recognition of influenza-associated pulmonary aspergillosis and, more recently, COVID-19-associated pulmonary aspergillosis.

The treatment landscape for haematological malignancies has changed considerably in recent years, and some recently introduced targeted agents, such as ibrutinib, are increasing the risk of invasive fungal infections. Consideration must also be given to the risk of drug–drug interactions between mould-active azoles and small-molecule kinase inhibitors.

At the same time, infections caused by rare moulds and yeasts are increasing, and diagnosis continues to be challenging. There is growing concern about azole resistance among both moulds and yeasts, mandating continuous surveillance and personalized treatment strategies.

It is anticipated that the epidemiology of fungal infections will continue to change and that new populations will be at risk. Early diagnosis and appropriate treatment remain the most important predictors of survival, and broad-spectrum antifungal agents will become increasingly important. Liposomal amphotericin B will remain an essential therapeutic agent in the armamentarium needed to manage future challenges, given its broad antifungal spectrum, low level of acquired resistance and limited potential for drug–drug interactions.

Conceptual Framework and Methodological Challenges for Modeling Effectiveness in Oncology Treatment Sequence Models

In this review, we summarize the challenges faced by existing oncology treatment sequence decision models and introduce a general framework to conceptualize such models. In the proposed framework, patients with cancer receive at least two lines of therapy (LOTs) followed by palliative care throughout their lifetime. Patients cycle through progression-free and progressive disease health states in each LOT before death. Under this framework, four broad aspects of modeling effectiveness of treatment sequences need exploration. First, disease progression, treatment discontinuation, and the relationship between the two events should be considered. Second, the effectiveness of each LOT depends on its placement in a treatment sequence as the effectiveness of later LOTs may be influenced by the earlier LOTs. Third, the treatment-free interval (TFI; time between discontinuation of earlier LOT and initiation of later LOT) may impact a therapy's effectiveness. Fourth, in the absence of head-to-head trials directly comparing LOTs, indirect treatment comparison (ITC) of outcomes for a specific LOT or even for the entire treatment sequence is important to consider. A search of decision models that estimated effectiveness of at least two lines of oncology therapy was conducted in PubMed (N = 20) and technology appraisals by the National Institute for Health and Care Excellence (N = 26) to assess four methodological aspects related to the model framework: (1) selection of outcomes for effectiveness in a treatment sequence, (2) approaches to adjust the efficacy of a treatment in consideration of its place in the sequence, (3) approaches to address TFIs between LOTs, and (4) incorporation of ITCs to estimate comparators' effectiveness in the absence of direct head-to-head evidence. Most models defined health states based on disease progression on different LOTs while estimating treatment duration outside of the main model framework (30/46) and used data from multiple data sources in different LOTs to model efficacy of a treatment sequence (41/46). No models adjusted efficacy for the characteristics of patients who switched from an earlier LOT to a later LOT or adjusted for the impact of prior therapies, and just six models considered TFIs. While 11 models applied ITC results to estimate efficacy in comparator treatment sequences, the majority limited the ITC to one LOT in the sequence. Thus, there is substantial room to improve the estimation of effectiveness for treatment sequences using existing data when comparing effectiveness of alternative treatment sequences.

Novel Bis- and Mono-Pyrrolo[2,3-d]pyrimidine and Purine Derivatives: Synthesis, Computational Analysis and Antiproliferative Evaluation

Novel symmetrical bis-pyrrolo[2,3-d]pyrimidines and bis-purines and their monomers were synthesized and evaluated for their antiproliferative activity in human lung adenocarcinoma (A549), cervical carcinoma (HeLa), ductal pancreatic adenocarcinoma (CFPAC-1) and metastatic colorectal adenocarcinoma (SW620) cells. The use of ultrasound irradiation as alternative energy input in Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) shortened the reaction time, increased the reaction efficiency and led to the formation of exclusively symmetric bis-heterocycles. DFT calculations showed that triazole formation is exceedingly exergonic and confirmed that the presence of Cu(I) ions is required to overcome high kinetic requirements and allow the reaction to proceed. The influence of various linkers and 6-substituted purine and regioisomeric 7-deazapurine on their cytostatic activity was revealed. Among all the evaluated compounds, the 4-chloropyrrolo[2,3-d]pyrimidine monomer 5f with 4,4′-bis(oxymethylene)biphenyl had the most pronounced, although not selective, growth-inhibitory effect on pancreatic adenocarcinoma (CFPAC-1) cells (IC₅₀ = 0.79 µM). Annexin V assay results revealed that its strong growth inhibitory activity against CFPAC-1 cells could be associated with induction of apoptosis and primary necrosis. Further structural optimization of bis-chloropyrrolo[2,3-d]pyrimidine with aromatic linker is required to develop novel efficient and non-toxic agent against pancreatic cancer.

A Primer on RECIST 1.1 for Oncologic Imaging in Clinical Drug Trials

Drug discovery and approval in oncology is mediated by the use of imaging to evaluate drug efficacy in clinical trials. Imaging is performed while patients receive therapy to evaluate their response to treatment. Response criteria, specifically Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), are standardized and can be used at different time points to classify response into the categories of complete response, partial response, stable disease, or disease progression. At the trial level, categorical responses for all patients are summated into image-based trial endpoints. These outcome measures, including objective response rate (ORR) and progression-free survival (PFS), are characteristics that can be derived from imaging and can be used as surrogates for overall survival (OS). Similar to OS, ORR and PFS describe the efficacy of a drug. U.S. Food and Drug Administration (FDA) regulatory approval requires therapies to demonstrate direct evidence of clinical benefit, such as improved OS. However, multiple programs have been created to expedite drug approval for life-threatening illnesses, including advanced cancer. ORR and PFS have been accepted by the FDA as adequate predictors of OS on which to base drug approval decisions, thus substantially shortening the time and cost of drug development (1). Use of imaging surrogate markers for drug approval has become increasingly common, accounting for more than 90% of approvals through the Accelerated Approval Program and allowing for use of many therapies which have altered the course of cancer. Keywords: Oncology, Tumor Response  RSNA, 2021.

Electronic properties investigation of human dihydrofolate reductase complexes with ligands

Despite the fact that there are already drugs for cancer, they still show strong toxicity to the human organism. That is why it is necessary to establish the factors affecting activity in order to develop new, more effective drugs aimed at tumor cells, minimizing harm to healthy cells. The present research is based on electronic properties calculation of the complexes using AlteQ approach. In the focus of this study are complexes of human dihydrofolate reductase (hDHFR) with a series of known inhibitors bound in the active site. Further, a statistical analysis was performed to establish the relationships between a myriad electronic characteristics and IC₅₀. The change in total volume and the change of own electrons number of hydrogen atoms in their atomic basins are identified as the descriptors correlating the most with the hDHFR inhibition potency. Additionally, two lipophilic parts of protein (Thr56, Ser59, Ile60 and Ile7, Val8, Ala9) were found, which act as a key factor in decreasing bioactivity. The depth analysis of intermolecular interactions showed that the interactions between water molecules and ligand play a crucial role in hDHFR inhibition. Furthermore, the molecular dynamics simulations were used for deeper understanding of the structural inhibition, each for 50 ns time scale in explicit water conditions. Thus, the AlteQ approach made it possible to determine the factors influencing the activity and evaluate them not only qualitatively, but also quantitatively.Communicated by Ramaswamy H. Sarma.

The study of EGFR-ligand complex electron property relationship with biological activity

The present investigation grounded on estimation of electron properties of the structures of EGFR proteins-ligand complexes using our laboratory-developed methodology AlteQ approach, which describes the molecular electron density of the complex in space for a certain point in three-dimensional coordinates. Briefly, the system embodies molecular electron density as a sum of Slater's type atomic increments of the molecular system. Further, using this methodology, we calculated different electron characteristics of selected EGFR protein-ligand complexes and established the relationship between different electron properties with their experimental pharmacological activity value (pIC₅₀). The study suggested that EGFR inhibitory activity has higher correlation with intermolecular contacts of H with pi-system of aromatic ring between protein and ligands. Therefore, this created model has impact to identify and design potential ligands against EGFR in anticancer drug discovery.Communicated by Ramaswamy H. Sarma.