A medicine adoption model for assessing the expected effects of additional real-world evidence (RWE) at product launch

Figures & data

Figure 1. The medicine adoption model. Abbreviations. PH–: non-pharmaceutical company stakeholder groups; PH+: pharmaceutical company stakeholder groups.

Figure 2. Expected beneficial effect on time to maximal adoption (tmAd) of a new medicine when arriving at its launch with phase III and real-world evidence. Abbreviations. Comm, Commercial; MAcc, Market Access; MAff, Medical Affairs; Raff, Regulatory Affairs; Payo, Payors; Pres, Prescribers.

Figure 3. Expected beneficial effect on depth of maximal adoption (dmAd) of a new medicine when arriving at its launch with phase III and real-world evidence. Abbreviations. Comm, Commercial; MAcc, Market Access; MAff, Medical Affairs; Raff, Regulatory Affairs; Payo, Payors; Pres, Prescribers.

Figure 4. Expected beneficial effect on time to maximal adoption (tmAd) and depth of maximal adoption (dmAd) of a new medicine when arriving at its launch with phase III and real-world evidence. Abbreviaitons. Comm, Commercial; MAcc, Market Access; MAff, Medical Affairs; Raff, Regulatory Affairs; Payo, Payors; Pres, Prescribers.

Table 1. Analysis of SRs above the consensus threshold for inclusion (CI > 0.50) in ≥ 4 SHGs and their heterogeneity of consensus scores regarding the time to maximal adoption (tmAd).

Reduction in time to maximal adoption (tmAd)			Vs. depth of maximal adoption (dmAd)	Adoption system		No. SHGs aware of SR	No. SHGs with CS = 1 or 2 on SR	The proportion of SRs reaching CI > 0.50	Overall heterogeneity (p-value)	PH– vs. PH +  heterogeneity (p-value)
				Input/ logic	Gatekeeper (subsystem)
SR ID	Partner	Supporting Rationales (SR)
2		Increase in volume of evidence in non-clinical trial outcomes	Unique	Input	NoS	6	6	100	.006*	.207
27	2	Increase in volume of evidence on safety	Common	Input	NoS	6	6	100	.006*	.207
28	3	Increase in the volume of evidence on the effectiveness	Common	Input	NoS	6	6	100	.006*	.207
8	30	Encourages prescribers to prescribe	Common	Logic	Pres	6	5	83	<.001*	.001*
1		Increase in volume of evidence in clinical trial outcomes	Unique	Input	NoS	5	5	100	.999	NANA
3		Increase in volume of evidence in non-clinical trial/ broader real-world populations	Unique	Input	Pres	5	5	100	.015*	.685
12	5	Increase in volume of the burden of disease evidence	Aligned	Input	NoS	5	5	100	.113	.999
13	13	Increase in the volume of evidence on the standard of care	Common	Input	NoS	5	5	100	.113	.596
10	12	Encourages payors to grant initial reimbursement	Common	Logic	Payo	4	4	100	.345	.999
14	8	Encourages regulators to grant approval	Common	Logic	Regu	4	4	100	.228	.661
18		Assists pricing negotiations	Unique	Logic	Payo	4	4	100	.999	NANA
19		Reduces payor uncertainty	Unique	Logic	Payo	4	4	100	.822	.999
26	1	Increases applicability of evidence to real-world patients in the clinic	Common	Logic	Pres	4	4	100	.016*	.585
7		Influences clinicians to a greater degree than clinical trials	Unique	Logic	Pres	5	3	60	<.001*	.072
9		Encourages prescribers to recommend peers to prescribe	Unique	Logic	Pres	4	3	75	.025*	.399

Abbreviations. Gatekeeper subsystems: NoS, Non-specific; Regu, Regulatory; Payo, Payor; Pres, Prescriber; CS, Consensus Score; CI, Consensus Index; PH+, Pharmaceutical company SHGs; PH–, Non-pharmaceutical company SHGs.

Table 2. Analysis of SRs above the consensus threshold for inclusion (CI > 0.50) in ≥ 4SHGs and their heterogeneity of consensus scores regarding the depth of maximal adoption (dmAd).

Increase in depth of maximal adoption (dmAd)			Vs. reduction in time to maximal adoption (tmAd)	Adoption system		No. SHGs Aware of SR	No. SHGs with CS = 1 or 2 on SR	Proportion of SRs Reaching CI > 0.50	Overall heterogeneity (p-value)	PH– vs. PH + heterogeneity (p-value)
				Input/ Logic	Gatekeeper (subsystem)
SR ID	Partner	Supporting rationales (SR)
2	27	Increases volume of evidence on safety	Common	Input	NoS	5	5	100	.063	.591
3	3	Increases volume of evidence on the effectiveness	Common	Input	NoS	5	5	100	.187	.294
5	13	Improves understanding burden of the disease	Aligned	Logic	NoS	4	4	100	.28	.999
7		Improves understanding of unmet patients' needs	Unique	Logic	Pres	4	4	100	.631	.514
1	29	Improves applicability of evidence to real-world patients	Common	Logic	NoS	4	3	75	.266	.659
8	15	Encourages regulators to grant approval	Common	Logic	Regu	4	3	75	.743	.999
10	17	Encourages regulators to approve a broader indication	Common	Logic	Regu	4	3	75	.46	.999

Abbreviations. Gatekeeper subsystems: NoS, Non-specific; Regu, Regulatory; Payo, Payor; Pres, Prescriber. CS, Consensus Score; CI, Consensus Index; PH+, Pharmaceutical company SHGs; PH-, Non-pharmaceutical company SHGs.

Table 3. Number of Unique Supporting Rationales (SRs) suggested by SHGs as a proportion of the total number of SRs suggested regarding time to maximal adoption (tmAd) and depth of maximal adoption (dmAd).

	SHG	Unique SRs (a)	Non-Unique SRs (b)	Total SRs (c)	a/c (%)	p-value	a/Total overall unique SRs^b (%)	a/total overall SRs^c (%)
Reduction in time to maximal adoption (tmAd)
PH–	Payo	0	16	16	0	.604	0	0
	Pres	1	11	12	8.33	.999	16.67	3.45
	Mean	0.5	13.5	14	3.57	NA	8.33	1.72
	Total	1	19	20	5	NA	NA	3.45
PH+	Comm	4	21	25	16	.049#	66.67	13.79
	MAcc	0	14	14	0	.686	0	0
	MAff	0	15	15	0	.643	0	0
	RAff	1	18	19	5.26	.999	16.67	3.45
	Mean	1.25	17	18.25	6.85	NA	20.83	4.31
	Total	9	19^a	28^c	31.03	NA	NA	31.03
Overall (PH + and PH-)	Total	6^b	23^c	29^c	21.43	NA	100	20.69
	Mean/SHG	1	15.83	16.83	5.94	NA	16.67	3.45
	Total^a	10	19	29	34.48	NA	NA	34.48
Increase in depth of maximal adoption (dmAd)
PH–	Payo	2	8	10	20	.999	13.33	5.71
	Pres	0	7	7	0	.364	0	0
	Mean	1	7.5	8.5	11.76	NA	6.67	2.86
	Total	2	12^a	14^c	14.29	NA	NA	5.71
PH+	Comm	6	16	22	27.27	.51	40	17.14
	MAcc	1	8	9	11.11	.774	6.67	2.86
	MAff	1	13	14	7.14	.323	6.67	2.86
	RAff	5	7	12	41.67	.105	33.33	14.29
	Mean	3.25	11	14.25	22.81	NA	21.67	9.29
	Total	21	12^a	33^c	63.64	NA	NA	60
Overall (PH + and PH–)	Total	15^b	20^c	35^c	42.86	NA	100	42.86
	Mean/SHG	2.5	9.83	12.33	20.28	NA	16.67	7.14
	Total^a	23	12	35	65.71	NA	NA	65.71

Abbreviations. SHG^, Stakeholder Group; SH, Stakeholder; SR, Supporting Rationale; Comm, Commercial; MAcc, Market Access; MAff, Medical Affairs; Raff, Regulatory Affairs; Payo, Payors; Pres, Prescribers.

^aNumbers presented for combined populations of non-pharma and pharma stakeholder groups.

^bTotal overall supporting rationales unique to any one stakeholder group only.

^cTotals are adjusted for the overlapping number of supporting rationales in combined populations of stakeholder groups.

Table 4. Supporting Rationales (SRs) for expected effect sizes by subsystem, commonality and mode of effect: via input or logic.

Effect	Gatekeeper (subsystems)				p-value	SR			Effect		Total SR n
	Regu n (%)	Payo n (%)	Pres n (%)	NoS n (%)		Unique n (%)	Common n (%)	Aligned n (%)	Input	Logic
tmAd	3	6	13	6	.012^c	16	9	3	8	20	28
	(10.71%)	(21.43%)	(46.43%)	(21.43%)		(57.14%)	(32.14%)	(10.71%)	(28.57%)	(71.43%)
dmAd	4	7	5	19	.263	23	9	3	9	26	35
	(11.43%)	(20%)	(14.29%)	(54.29%)		(65.71%)	(25.71%)	(8.57%)	(25.71%)	(74.29%)

^cThe dominance of Pre SHG in its nominations as contributing to the overall SR for beneficial effect in the Gatekeeper subsystems was tested and was found to be statistically significant. The dominance of Payo SHG in its nominations as contributing to the overall SR for beneficial effect was tested in dmAd. However, this was found not to be statistically significant.

Abbreviations. SHG, Stakeholder group; SH, Stakeholder; SR, Supporting Rationale; Comm, Commercial; MAcc, Market Access; MAff, Medical Affairs; Raff, Regulatory Affairs; Payo, Payors; Pres, Prescribers.

Data availability statement

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.