生技製藥產業鑑價模式之研究:實質選擇權之應用

葉姿吟(Tzu-Yin Yeh)

指導教授 ： 李吉仁

國立臺灣大學/管理學院/國際企業學研究所/碩士(2005年)

https://doi.org/10.6342/NTU.2005.03010

摘要

對生技製藥產業而言，鑑價扮演相當重要的角色。許多經濟活動，包括：募資、增資、授權、拍賣，都需以技術鑑價為基礎及判斷依據。然而，由於生技製藥產業研發成本高、存在許多不確定性因素，新藥研發到上市必須投入相當的研發成本，也由於研發過程時間長，充滿高度不確定性，加上新藥開發到正式上市獲利，往往需要10-15年的時間，於這段期間決策者往往會依據該計畫的成功率、可行性、未來市場狀況，不斷調整其決策，選擇放棄或提前執行該計畫，因此，採用一般傳統評價法將無法呈現此決策彈性價值。
有鑑於此，本論文以實質選擇權法（real options approach）概念出發，並以美式選擇權作為評價模式，利用最小平方蒙地卡羅模擬法（least square Monte Carlo simulation）計算一新藥開發計畫的合理價值，除了考量財務面相關參數，本文亦考慮技術、市場環境、潛在競爭者的進入、專利權保護期限等因素，使評價模型更貼近產業實際情況，同時以實質選擇權法與一般傳統淨現值法評價此計畫價值，結果證明以實質選擇權評價生技製藥產業較一般傳統淨現值法適切。
最後，藉由參數的敏感度分析找出影響實質選擇權價值的重要變數，由敏感度分析的結果來看，期初期望投資完成成本K、期初預估現金流量C、現金流量不確定性ψ、對手進入市場的機率λ、對手進入市場現金流量乘數ω、現金流量趨勢項α以及專利權保護期限T，都是相對關鍵的參數，與生技製藥產業產業特性不謀而合，證明評價過程除了財務面變數外，產業的競合、策略互動必須納入模型考量使得評價結果更切合實際。

關鍵字

實質選擇權 ； 生技製藥產業 ； 最小平方蒙地卡羅模擬法

並列摘要

In the biotech pharmaceutical industry, evaluation plays a vital role in various stages of a product life cycle, from initial fund raising, seasoned equity offering, authorization, to the auctioning of patents, which must be based on appropriate evaluation tools. However, as drug discovery normally incurs high R&D costs and involves high uncertainty from various sources, the invested company shall have a certain degree of decision flexibility to adjust their strategies, even abandon the project during investing period. Therefore, an adequate evaluation approach shall reflect this kind of decision nature and flexibility. Unfortunately, the traditional net present value approach cannot satisfy such an evaluation need.
The purpose of the present research is to apply the real options approach to the case of biopharmaceutical evaluation. We adopt American option method to evaluate a new drug development project and use the Least Squares Monte Carlo Simulation to price the options. In addition to financial parameters, we also consider some industry-level parameters, including technological uncertainty, industry dynamics, potential new entrants, patent term, which significantly influences the project value. Our result shows that by incorporating these factors our model shows a higher degree of robustness than the net present value method.
According to the results of sensitivity analyses, we further find that parameters of initial expected cost (K), initial expected cash flow (C),uncertainty in the cash flow (φ), the probability of new entrants (λ), the effect of cash flow of new entrants (ω), the draft (α)（economic growth rate）, patent term (T) are critical to the valuation. These key parameters are highly relevant to the valuation in biopharmaceutical industry. In short, our research indicates that in addition to financial parameters effective evaluation models shall take strategic interaction and industry uncertainty into their considerations.

並列關鍵字

Real Options ； biotech pharmaceutical industry ； Least Squares Monte Carlo Simulation (LSM)

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