PharmaBlock Sciences (Nanjing), Inc (300725) Fair Value & Analysis
Healthcare · CN · Market cap 7.5B CNY
Analysis
PharmaBlock Sciences (Nanjing), Inc (300725) currently trades at ¥33.75, while our model-based Fair Value estimate is ¥19.31 — implying the stock looks roughly 42.8% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
PharmaBlock Sciences (Nanjing), Inc. provides chemistry products and services throughout the pharmaceutical research and development, and commercial manufacturing in China and internationally. It offers medicinal chemistry-oriented SAR/SPR tool kits for molecule design; building blocks enabled libraries, including fragment-based drug discovery, DNA encoded library technology, and mega virtual library screening to support the discovery of novel hit compounds; custom synthesis (FFS); and full time equivalent (FTE). The company also provides small molecule drug substance CDMO services, including optimal route scouting; FFS and FTE for process research and development of RSMs, intermediates, and APIs; impurity studies and synthesis; solid state chemistry; analytical development and quality control; cGMP manufacturing of intermediates and APIs; and CMC regulatory filing support. In addition, it offers small molecule DP CDMO services, such as candidate screening and selection, early devel…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.