Is the $1000 Genome as Near as We Think Is the $1000 Genome as Near as We Think? A Cost Analysis of Next-Generation Sequencing K.JM. van Nimwegen, R.A. van Soest, J. A. Veltman, M. R. Nelen, G. J. van der Wilt, L. ELM. Vissers, and J. PC. Grutters November 2016 www.clinchem.org/content/62/11/1458.full © Copyright 2016 by the American Association for Clinical Chemistry

Introduction Technological advancements and simultaneously dropping costs of next-generation sequencing (NGS) have taken place in recent years Commercial parties claim to be able to sequence an entire human genome for < $1,000 However, a complete and valid cost overview of NGS applications is currently lacking Objective: to provide a complete, and up-to-date overview of the real costs of three NGS applications: Targeted gene panels, whole exome sequencing, and whole genome sequencing

Question 1 Why would breaking the $1,000 genome barrier be such a breakthrough? Which consequences would this have?

Methods (I) Cost calculations were based on list prices, and the following assumptions: TGP WES WGS Platform NextSeq 500 HiSeq4000 HiSeqX5 Life cycle (years) 5 Average coverage 100x 70x 30x Utilization rate 10% 75% Data storage (Gb/sample) 1 150 600 Data storage (years) Table 1. Base case assumptions. TGP = targeted gene panel; WES = whole exome sequencing; WGS = whole genome sequencing

Methods (II) Costs were divided into three categories: Capital costs (non-recurring costs for equipment) Maintenance costs Operational costs (costs for running the sample) All costs were calculated per sample

Methods (III) Sensitivity analyses to anticipate future cost developments From these, a best case and worst case scenario were constructed  Lower and upper bound of NGS costs TGP WES WGS Capital costs - 50% Consumable costs Life cycle 3 – 5 years Average coverage 30x – 100x Utilization 1% - 15% 55% - 95% Table 2. Sensitivity analyses

Question 2 What can you say about the transferability of the results of this study between laboratories within and between countries? And how can you deal with cost components that aren’t directly transferable?

Results (I) Costs in euro’s TGP WES WGS Capital costs 1.89 35.19 175.33 Maintenance costs 0.91 12.29 72.04 Operational costs 330.10 744.27 1,421.64 Obtaining and extracting DNA 42.17 Sample preparation 242.62 296.68 27.61 Sequencing 4.56 262.24 1,057.81 Lab personnel 8.97 70.08 Data processing and storage 0.55 10.75 130.00 Data interpretation and report 31.23 62.65 93.97 Total per-sample costs €333 €792 €1,669 Table 3. Per-sample costs of TGP, WES, and WGS. TGP = targeted gene panel; WES = whole exome sequencing; WGS = whole genome sequencing

Results (II) Costs in euros TGP WES WGS Base case 333 792 1,669 Capital costs -50% 332 775 1,582 Consumable costs -50% 209 513 1,126 Life cycles of 3 years 334 810 1,761 30x coverage 328 615 100x coverage 929 5,430 Lower utilization (1%; 55%; 55%) 358 809 1,759 Higher utilization (15%; 95%; 95) 782 1,617 Table 4. Sensitivity analyses

Results (III) Costs in euros TGP WES WGS Capital costs -50% Current Consumable costs Life cycle (years) 5 3 Utilization 15% 95% 1% 55% Required coverage 30x 100x Per-sample costs (€) 205 401 1,006 368 989 6,157 Table 5. Best case and worst case scenario analyses

Question 3 What is needed to achieve the $1,000 genome in the future? How likely is it that this is going to happen, and why?

Discussion This study included a complete, and up-to-date overview of the costs of diagnostic NGS applications $1,000 genome not yet achieved Only approached in very optimistic best case scenario Per sample costs of WGS considerably higher than WES and TGP. This does not imply that WGS should not be used in clinical practice. Choice of NGS application depends also on its effectiveness (diagnostic yield). For each patient population, the choice of NGS applications and sequencing depth should be based on a careful trade-off between costs and consequences for the patient