Implementation aspects of expensive therapies: Coverage with real world data (RWD) collection using the example of SMA therapies

Research area: HTA-methods & steering instruments

Project management part 1: Kathrin Wohlhöfner, Claudia Wild
Project management part 2: Judit Erdös, Claudia Wild
Project management part 3: Christoph Strohmaier, Judit Erdös, Claudia Wild
Duration: February to June (Part 1), July to August (Part 2), August to October (Part 3)
Language: English (with German summary)

Background:  It is predicted that approximately 2-4 new Advanced Therapies Medicinal Products (ATMPs) will be brought to the market each year.  According to the Alliance of Regenerative Medicine (ARM) annual report 2020 more than 1,220 clinical trials worldwide are investigating ATMPs for various diseases, 152 of which are already in phase 3 trials (1). ATMP is the umbrella term of three medicinal product classes, somatic cell therapeutics, gene therapeutics, and bioengineered tissue preparations [also called tissue engineered products (TEPs)], as well as combination products (2). These drugs are characterized by a high degree of complexity. The R&D area of ATMP is still young: the development of ATMPs is mostly characterized by a highly experimental character and often finds its origin in academic research environments such as universities and their hospitals. Chimeric antigen receptor (CAR) T-cell therapy, for example, is based on genetically engineered T cells and is a new type of personalized cellular immunotherapy. 13 CAR T-cell therapies are currently in an advanced development status (3).  Gene therapy drugs contain "recombinant" genes that are introduced into the body and targeted against a variety of genetic disorders. 32 gene therapies in eight different indications are currently in an advanced development status (4).

Since there is (often) little evidence about the actual patient-relevant benefits and long-term effects at the time of approval, but great expectations among patients and the need for fair access to potentially effective therapies on the one hand, but also – due to the extremely high costs – the need for a monitoring of the realizable and realized short- and medium-term benefits for patients is evident. For this reason, many western countries have started to set up coverage with evidence generation systems (or Outcome Based Managed Entry Agreements/ OBMEA) to collect real world data on patients´ benefits (5), which allow the conditional reimbursement of such therapies  (6).

Objective and Research Questions (FF):

The aim of the project is, on the one hand, to develop a generic organizational model (work steps, processes, responsibilities, data infrastructure and sovereignty) for such real world data (RWD) collections on very expensive (gene, ATMP) therapies and, on the other hand, to test it on a case study (spinal muscular atrophy). 

RQ1: What (theoretical) frameworks for building such models for reimbursement with real world data collection exist internationally? What are their similarities and differences?

RQ2: What modules or elements (data infrastructure/registry, processes/SOPs, responsibilities) are these models/frameworks composed of?

RQ3: For which (gene therapy, regenerative) therapies are these models/frameworks applied and what is the experience?

RQ4: What can be learned from countries that are more advanced in applying such reimbursement models?

Method Part 1: Systematic synthesis of models for the introduction of therapies under real world data documentation, synopsis of international experiences.

• Identification of international models
• Semi-structured interviews (n=?10)
• Analysis of work steps, processes, responsibilities, data infrastructure and sovereignty, etc.

Part 2: Results of therapies for spinal muscular atrophy (SMA) from published studies

RQ1: What medium- and long-term outcomes ? 12 months on SMA therapies for SMA 1, SMA 2-3, SMA 4 are reported in published studies?

RQ2: What endpoints are reported in published studies and what instruments are used to collect these endpoints?

Method Part 2:  

• Systematic review on medium- and long-term outcomes ? 12 months on SMA therapies:  (Spinraza, Zolgensma and combination therapies of both, possibly also Evrysdi[1] ).

Inclusion criteria for the systematic literature search:

Population	Pateints with: SMA type 1, 2+3, 4
Intervention	Spinraza, Zolgensma Combination therapies of Spinraza, Zolgensma Evrysdi
Comparators	Standard of Care (SoC)
Outcomes	Outcomes with ? 12 months follow-up. Motor endpoints (HINE, CHOP-INTEND, HFSME, RULM) Quality of life endpoints Safety endpoints (adverse events: AE, SAE)
Study design	Any study design: retrospective, prospective case series, registry studies.
Publication period	2017 until May 2021
Language	German, English

Part 3a: Results of spinal muscular atrophy (SMA) therapies from application-accompanying data collection.

RQ1: What are the medium- and long-term outcomes ? 12 months on SMA therapies in SMA 1, SMA 2-3, SMA 4 shown by the real world data collection of Austrian patients?

RQ2: Are there differences and similarities between the results from published studies and from the real world data collection?

Part 3b: Differences and similarities of the "ideal" vs. "real" model of data collection

RQ3: How does the real world data collection on SMA therapies compare to the generic model: what are the advantages and disadvantages based on the specific example of real world data collection on SMA therapies?

Method Part 3a + 3b:

1. Data analysis of anonymized mid- and long-term outcomes of SMA therapies in Austrian patients: descriptive processing of raw data.
2. Contrasting the results from real world data collection (in SMArtCARE) with published results (efficacy vs. effectiveness): testing differences in endpoints (statistical tests of raw data from Austria vs. study data), comparison of patient characteristics, comparison of treatment dropouts, etc.
3. Interviews with SMA therapists (2-4 Austrian neuro-pediatricians) and process analysis according to work steps and responsibilities of real world data collection on SMA therapies analogous to the generic model with a focus on advantages and disadvantages of organizational aspects.

Schedule/Milestones:

Time period	Task
February-March	Part 1: Identification of models by means of systematic and hand search in literature as well as INAHTA contacts, selection of relevant models, identification of interview partners, preparation of an interview guide.
April-May	Part 1: Conducting 10 interviews on models application-accompanying data collection, transcription, literature analysis.
June	Part 1: Analysis of interviews and synthesis of information from literature and inteviews, reporting on process steps. Part 2: Systematic literature search on medium and long-term outcomes of SMA therapies.
July-August	Part 2: Extraction of data on results in published studies, writing of report Part 3: Acquisition of data on Austrian patients, development of an analysis grid
September-October	Part 2: Internal and external review, revision, finalization. Part 3a: Analysis of data on Austrian patients, analysis of differences/ commonalities of results, report writing Part 3b: Interviews and process analysis, report writing
November	Internal and external review, revision, finalization

References

1. Alliance for Regenerative Medicine (ARM). Advancing Gene, Cell & Tissue-Based Therapies. Annual Report 2020. http://alliancerm.org/wp-content/uploads/2021/03/ARM_AR2020_FINAL-PDF.pdf
2. Eder C, Wild C (2019): Technology forecast: Advanced therapies in late clinical research, EMA approval or clinical application via Hospital exemption. Journal of Market Access & Health Policy. https://www.tandfonline.com/doi/full/10.1080/20016689.2019.1600939
3. Geiger-Gritsch, S. (2020): CAR-T Zelltherapien in Entwicklung, Horizon Scanning: CAR-T Zelltherapie. AIHTA Policy Brief 006a. https://eprints.aihta.at/1268/1/Policy_Brief_006a.pdf
4. Wild, C., Wohlhöfner, K., Sehic, O. und Grössmann, N. (2020): ATMP- und Gentherapien in Entwicklung, Horizon Scanning, AIHTA Policy Brief 006b. https://eprints.aihta.at/1269/1/Policy_Brief_006b.pdf

 

1. IQWIG (2020): Konzept für eine anwendungsbegleitende Datenerhebung – Onasemnogen-Abeparvovec ,  IQWiG-Bericht Nr. 977,  a20-61_anwendungsbegleitende-datenerhebung-onasemnogen-abeparvovec_rapid-report_v1-0.pdf
2. IMPACT HTA: implementation of Outcome Based Managed Entry Agreements to help demonstration of value of orphan medicinal products, https://www.impact-hta.eu/work-package-10