For 2021: NGS: $1.5B, Microfluidics: $1B, CRISPR: $0.5B → total $3B. Then each year increases by the CAGR. For 2022: NGS $1.8B, Microfluidics $1.2B, CRISPR $0.6B → total $3.6B. Continuing this up to 2033. But the user's example uses numbers like [10,12,15,18,20], etc. So maybe the values are in USD billion, and the total per year is the market size. So for each year, the sum of the three segments equals the market size. Given the 2023 market size is $6.2B, the 2025 base year would be higher. Let me structure the data accordingly. For example, in 2025, the market size is $8.5B. Then for each segment, their shares. Let's say NGS is $4.25B (50%), Microfluidics $3B (35%), CRISPR $1.25B (15%). Then project growth based on CAGR. The values for the chart would then be arrays per segment for each year from 2021 to 2033. But this requires creating a realistic growth curve. Since the CAGR is 22.5%, the market size grows from $3B in 2021 to $53B in 2033 (assuming 10 years). But that seems too high. Wait, if the current size is $6.2B in 2023, with a CAGR of 22.5%, by 2033 it would be 6.2*(1.225)^10 ≈ 6.2*8.3 ≈ $51.5B. So in 2025, it's around $6.2*(1.225)^2 ≈ $6.2*1.500 ≈ $9.3B. So the base year 2025 is $9.3B. Then the forecast period (2026-2033) would go up to $51.5B. But the chart needs data from 2021 to 2033. Let me create a realistic data set for each year, ensuring the segments' growth aligns with the overall market growth. For example, NGS could be the leading segment, growing faster than others. Microfluidics also growing, and CRISPR-based techs maintaining a smaller share. Assigning values accordingly. This requires some estimation, but I'll proceed with the numbers in the JSON example but adjusted for real data.
</think>
